From b98af44fcf89b9946e1de438b1f5527e6bf28905 Mon Sep 17 00:00:00 2001 From: Ivan Shapovalov Date: Sat, 22 Oct 2016 05:14:19 +0300 Subject: treewide: use C++ exceptions properly Since the codebase is designed around proper C++ idioms such as RAII, it makes sense to only use C++ exceptions internally instead of mixing exceptions and error codes. The exceptions are now caught at top level to preserve compatibility with the existing error code-based API. Note that we deliberately do not catch C++ runtime errors (such as `std::bad_alloc`) nor logic errors (aka failed assertions) because no actual handling can ever happen for such errors. However, in the C interface we do catch _all_ exceptions (...) and convert them into a wild-card error code. --- src/routines/level3/xgemm.cpp | 299 +++++++++++++++++++---------------------- src/routines/level3/xgemm.hpp | 48 +++---- src/routines/level3/xhemm.cpp | 132 +++++++++--------- src/routines/level3/xhemm.hpp | 14 +- src/routines/level3/xher2k.cpp | 286 ++++++++++++++++++--------------------- src/routines/level3/xher2k.hpp | 14 +- src/routines/level3/xherk.cpp | 196 +++++++++++++-------------- src/routines/level3/xherk.hpp | 12 +- src/routines/level3/xsymm.cpp | 132 +++++++++--------- src/routines/level3/xsymm.hpp | 14 +- src/routines/level3/xsyr2k.cpp | 214 ++++++++++++++--------------- src/routines/level3/xsyr2k.hpp | 14 +- src/routines/level3/xsyrk.cpp | 164 ++++++++++------------ src/routines/level3/xsyrk.hpp | 12 +- src/routines/level3/xtrmm.cpp | 134 +++++++++--------- src/routines/level3/xtrmm.hpp | 12 +- 16 files changed, 792 insertions(+), 905 deletions(-) (limited to 'src/routines/level3') diff --git a/src/routines/level3/xgemm.cpp b/src/routines/level3/xgemm.cpp index 1602c69f..a6f7c286 100644 --- a/src/routines/level3/xgemm.cpp +++ b/src/routines/level3/xgemm.cpp @@ -50,17 +50,17 @@ Xgemm::Xgemm(Queue &queue, EventPointer event, const std::string &name): // The main routine template -StatusCode Xgemm::DoGemm(const Layout layout, - const Transpose a_transpose, const Transpose b_transpose, - const size_t m, const size_t n, const size_t k, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, - const T beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { +void Xgemm::DoGemm(const Layout layout, + const Transpose a_transpose, const Transpose b_transpose, + const size_t m, const size_t n, const size_t k, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, + const T beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { // Makes sure all dimensions are larger than zero - if ((m == 0) || (n == 0) || (k == 0)) { return StatusCode::kInvalidDimension; } + if ((m == 0) || (n == 0) || (k == 0)) { throw BLASError(StatusCode::kInvalidDimension); } // Computes whether or not the matrices are transposed in memory. This is based on their layout // (row or column-major) and whether or not they are requested to be pre-transposed. Note @@ -99,12 +99,9 @@ StatusCode Xgemm::DoGemm(const Layout layout, // matrix A cannot be less than K when rotated, or less than M when not-rotated // matrix B cannot be less than N when rotated, or less than K when not-rotated // matrix C cannot be less than N when rotated, or less than M when not-rotated - auto status = TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); - if (ErrorIn(status)) { return status; } - status = TestMatrixB(b_one, b_two, b_buffer, b_offset, b_ld); - if (ErrorIn(status)) { return status; } - status = TestMatrixC(c_one, c_two, c_buffer, c_offset, c_ld); - if (ErrorIn(status)) { return status; } + TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); + TestMatrixB(b_one, b_two, b_buffer, b_offset, b_ld); + TestMatrixC(c_one, c_two, c_buffer, c_offset, c_ld); // Selects which version of GEMM to run const auto do_gemm_direct = (m * n * k < db_["XGEMM_MIN_INDIRECT_SIZE"]); @@ -131,7 +128,7 @@ StatusCode Xgemm::DoGemm(const Layout layout, // requirements, but several pre and post-processing kernels take care of those. However, the // overhead of these extra kernels might not be ideal for certain devices/arguments. template -StatusCode Xgemm::GemmIndirect(const size_t m, const size_t n, const size_t k, +void Xgemm::GemmIndirect(const size_t m, const size_t n, const size_t k, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, @@ -142,8 +139,6 @@ StatusCode Xgemm::GemmIndirect(const size_t m, const size_t n, const size_t k const size_t a_one, const size_t a_two, const bool a_want_rotated, const size_t b_one, const size_t b_two, const bool b_want_rotated, const size_t c_one, const size_t c_two, const bool c_want_rotated) { - auto status = StatusCode::kSuccess; - // Calculates the ceiled versions of m, n, and k const auto m_ceiled = Ceil(m, db_["MWG"]); const auto n_ceiled = Ceil(n, db_["NWG"]); @@ -158,109 +153,95 @@ StatusCode Xgemm::GemmIndirect(const size_t m, const size_t n, const size_t k const auto c_one_i = (c_want_rotated) ? n_ceiled : m_ceiled; const auto c_two_i = (c_want_rotated) ? m_ceiled : n_ceiled; - // The padded/transposed input/output matrices: if memory allocation fails, throw an exception - try { - - // Loads the program from the database - const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); - - // Determines whether or not temporary matrices are needed - auto a_no_temp = a_one == a_one_i && a_two == a_two_i && a_ld == a_one && a_offset == 0 && - a_do_transpose == false && a_conjugate == false; - auto b_no_temp = b_one == b_one_i && b_two == b_two_i && b_ld == b_one && b_offset == 0 && - b_do_transpose == false && b_conjugate == false; - auto c_no_temp = c_one == c_one_i && c_two == c_two_i && c_ld == c_one && c_offset == 0 && - c_do_transpose == false; - - // Creates the temporary matrices - const auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, a_one_i*a_two_i); - const auto b_temp = (b_no_temp) ? b_buffer : Buffer(context_, b_one_i*b_two_i); - const auto c_temp = (c_no_temp) ? c_buffer : Buffer(context_, c_one_i*c_two_i); - - // Events of all kernels (including pre/post processing kernels) - auto eventWaitList = std::vector(); - auto emptyEventList = std::vector(); - - // Runs the pre-processing kernel for matrix A. This transposes the matrix, but also pads zeros - // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In - // case nothing has to be done, these kernels can be skipped. - if (!a_no_temp) { - auto eventProcessA = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, - a_one, a_two, a_ld, a_offset, a_buffer, - a_one_i, a_two_i, a_one_i, 0, a_temp, - ConstantOne(), program, - true, a_do_transpose, a_conjugate); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventProcessA); - } - - // As above, but now for matrix B - if (!b_no_temp) { - auto eventProcessB = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList, - b_one, b_two, b_ld, b_offset, b_buffer, - b_one_i, b_two_i, b_one_i, 0, b_temp, - ConstantOne(), program, - true, b_do_transpose, b_conjugate); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventProcessB); - } - - // As above, but now for matrix C. This is only necessary if C is used both as input and output. - if (!c_no_temp && beta != static_cast(0)) { - auto eventProcessC = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, - c_one, c_two, c_ld, c_offset, c_buffer, - c_one_i, c_two_i, c_one_i, 0, c_temp, - ConstantOne(), program, - true, c_do_transpose, false); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventProcessC); - } - - // Retrieves the Xgemm kernel from the compiled binary - try { - auto kernel = Kernel(program, "Xgemm"); - - // Sets the kernel arguments - kernel.SetArgument(0, static_cast(m_ceiled)); - kernel.SetArgument(1, static_cast(n_ceiled)); - kernel.SetArgument(2, static_cast(k_ceiled)); - kernel.SetArgument(3, GetRealArg(alpha)); - kernel.SetArgument(4, GetRealArg(beta)); - kernel.SetArgument(5, a_temp()); - kernel.SetArgument(6, b_temp()); - kernel.SetArgument(7, c_temp()); - - // Computes the global and local thread sizes - const auto global = std::vector{ - (c_one_i * db_["MDIMC"]) / db_["MWG"], - (c_two_i * db_["NDIMC"]) / db_["NWG"] - }; - const auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; - - // Launches the kernel - auto eventKernel = Event(); - auto eventPointer = (!c_no_temp) ? eventKernel.pointer() : event_; - status = RunKernel(kernel, queue_, device_, global, local, eventPointer, eventWaitList); - if (ErrorIn(status)) { return status; } - - // Runs the post-processing kernel if needed - if (!c_no_temp) { - eventWaitList.push_back(eventKernel); - status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, - c_one_i, c_two_i, c_one_i, 0, c_temp, - c_one, c_two, c_ld, c_offset, c_buffer, - ConstantOne(), program, - false, c_do_transpose, false); - if (ErrorIn(status)) { return status; } - } - - // Successfully finished the computation - return StatusCode::kSuccess; - } catch (...) { return StatusCode::kInvalidKernel; } - } catch (...) { return StatusCode::kTempBufferAllocFailure; } + // Loads the program from the database + const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); + + // Determines whether or not temporary matrices are needed + auto a_no_temp = a_one == a_one_i && a_two == a_two_i && a_ld == a_one && a_offset == 0 && + a_do_transpose == false && a_conjugate == false; + auto b_no_temp = b_one == b_one_i && b_two == b_two_i && b_ld == b_one && b_offset == 0 && + b_do_transpose == false && b_conjugate == false; + auto c_no_temp = c_one == c_one_i && c_two == c_two_i && c_ld == c_one && c_offset == 0 && + c_do_transpose == false; + + // Creates the temporary matrices + const auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, a_one_i*a_two_i); + const auto b_temp = (b_no_temp) ? b_buffer : Buffer(context_, b_one_i*b_two_i); + const auto c_temp = (c_no_temp) ? c_buffer : Buffer(context_, c_one_i*c_two_i); + + // Events of all kernels (including pre/post processing kernels) + auto eventWaitList = std::vector(); + auto emptyEventList = std::vector(); + + // Runs the pre-processing kernel for matrix A. This transposes the matrix, but also pads zeros + // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In + // case nothing has to be done, these kernels can be skipped. + if (!a_no_temp) { + auto eventProcessA = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, + a_one, a_two, a_ld, a_offset, a_buffer, + a_one_i, a_two_i, a_one_i, 0, a_temp, + ConstantOne(), program, + true, a_do_transpose, a_conjugate); + eventWaitList.push_back(eventProcessA); + } + + // As above, but now for matrix B + if (!b_no_temp) { + auto eventProcessB = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList, + b_one, b_two, b_ld, b_offset, b_buffer, + b_one_i, b_two_i, b_one_i, 0, b_temp, + ConstantOne(), program, + true, b_do_transpose, b_conjugate); + eventWaitList.push_back(eventProcessB); + } + + // As above, but now for matrix C. This is only necessary if C is used both as input and output. + if (!c_no_temp && beta != static_cast(0)) { + auto eventProcessC = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, + c_one, c_two, c_ld, c_offset, c_buffer, + c_one_i, c_two_i, c_one_i, 0, c_temp, + ConstantOne(), program, + true, c_do_transpose, false); + eventWaitList.push_back(eventProcessC); + } + + // Retrieves the Xgemm kernel from the compiled binary + auto kernel = Kernel(program, "Xgemm"); + + // Sets the kernel arguments + kernel.SetArgument(0, static_cast(m_ceiled)); + kernel.SetArgument(1, static_cast(n_ceiled)); + kernel.SetArgument(2, static_cast(k_ceiled)); + kernel.SetArgument(3, GetRealArg(alpha)); + kernel.SetArgument(4, GetRealArg(beta)); + kernel.SetArgument(5, a_temp()); + kernel.SetArgument(6, b_temp()); + kernel.SetArgument(7, c_temp()); + + // Computes the global and local thread sizes + const auto global = std::vector{ + (c_one_i * db_["MDIMC"]) / db_["MWG"], + (c_two_i * db_["NDIMC"]) / db_["NWG"] + }; + const auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; + + // Launches the kernel + auto eventKernel = Event(); + auto eventPointer = (!c_no_temp) ? eventKernel.pointer() : event_; + RunKernel(kernel, queue_, device_, global, local, eventPointer, eventWaitList); + + // Runs the post-processing kernel if needed + if (!c_no_temp) { + eventWaitList.push_back(eventKernel); + PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, + c_one_i, c_two_i, c_one_i, 0, c_temp, + c_one, c_two, c_ld, c_offset, c_buffer, + ConstantOne(), program, + false, c_do_transpose, false); + } } @@ -268,7 +249,7 @@ StatusCode Xgemm::GemmIndirect(const size_t m, const size_t n, const size_t k // The direct version of GEMM, requiring just one kernel, no pre or post-processing kernels. template -StatusCode Xgemm::GemmDirect(const size_t m, const size_t n, const size_t k, +void Xgemm::GemmDirect(const size_t m, const size_t n, const size_t k, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, @@ -281,46 +262,40 @@ StatusCode Xgemm::GemmDirect(const size_t m, const size_t n, const size_t k, const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); // Retrieves the proper XgemmDirect kernel from the compiled binary - try { - const auto name = (a_do_transpose) ? (b_do_transpose ? "XgemmDirectTT" : "XgemmDirectTN") : - (b_do_transpose ? "XgemmDirectNT" : "XgemmDirectNN"); - auto kernel = Kernel(program, name); - - // Sets the kernel arguments - kernel.SetArgument(0, static_cast(m)); - kernel.SetArgument(1, static_cast(n)); - kernel.SetArgument(2, static_cast(k)); - kernel.SetArgument(3, GetRealArg(alpha)); - kernel.SetArgument(4, GetRealArg(beta)); - kernel.SetArgument(5, a_buffer()); - kernel.SetArgument(6, static_cast(a_offset)); - kernel.SetArgument(7, static_cast(a_ld)); - kernel.SetArgument(8, b_buffer()); - kernel.SetArgument(9, static_cast(b_offset)); - kernel.SetArgument(10, static_cast(b_ld)); - kernel.SetArgument(11, c_buffer()); - kernel.SetArgument(12, static_cast(c_offset)); - kernel.SetArgument(13, static_cast(c_ld)); - kernel.SetArgument(14, static_cast(c_do_transpose)); - kernel.SetArgument(15, static_cast(a_conjugate)); - kernel.SetArgument(16, static_cast(b_conjugate)); - - // Computes the global and local thread sizes - const auto m_ceiled = Ceil(m, db_["WGD"]); - const auto n_ceiled = Ceil(n, db_["WGD"]); - const auto global = std::vector{ - (m_ceiled * db_["MDIMCD"]) / db_["WGD"], - (n_ceiled * db_["NDIMCD"]) / db_["WGD"] - }; - const auto local = std::vector{db_["MDIMCD"], db_["NDIMCD"]}; - - // Launches the kernel - auto status = RunKernel(kernel, queue_, device_, global, local, event_); - if (ErrorIn(status)) { return status; } - - // Successfully finished the computation - return StatusCode::kSuccess; - } catch (...) { return StatusCode::kInvalidKernel; } + const auto name = (a_do_transpose) ? (b_do_transpose ? "XgemmDirectTT" : "XgemmDirectTN") : + (b_do_transpose ? "XgemmDirectNT" : "XgemmDirectNN"); + auto kernel = Kernel(program, name); + + // Sets the kernel arguments + kernel.SetArgument(0, static_cast(m)); + kernel.SetArgument(1, static_cast(n)); + kernel.SetArgument(2, static_cast(k)); + kernel.SetArgument(3, GetRealArg(alpha)); + kernel.SetArgument(4, GetRealArg(beta)); + kernel.SetArgument(5, a_buffer()); + kernel.SetArgument(6, static_cast(a_offset)); + kernel.SetArgument(7, static_cast(a_ld)); + kernel.SetArgument(8, b_buffer()); + kernel.SetArgument(9, static_cast(b_offset)); + kernel.SetArgument(10, static_cast(b_ld)); + kernel.SetArgument(11, c_buffer()); + kernel.SetArgument(12, static_cast(c_offset)); + kernel.SetArgument(13, static_cast(c_ld)); + kernel.SetArgument(14, static_cast(c_do_transpose)); + kernel.SetArgument(15, static_cast(a_conjugate)); + kernel.SetArgument(16, static_cast(b_conjugate)); + + // Computes the global and local thread sizes + const auto m_ceiled = Ceil(m, db_["WGD"]); + const auto n_ceiled = Ceil(n, db_["WGD"]); + const auto global = std::vector{ + (m_ceiled * db_["MDIMCD"]) / db_["WGD"], + (n_ceiled * db_["NDIMCD"]) / db_["WGD"] + }; + const auto local = std::vector{db_["MDIMCD"], db_["NDIMCD"]}; + + // Launches the kernel + RunKernel(kernel, queue_, device_, global, local, event_); } // ================================================================================================= diff --git a/src/routines/level3/xgemm.hpp b/src/routines/level3/xgemm.hpp index 46e12453..c61611b6 100644 --- a/src/routines/level3/xgemm.hpp +++ b/src/routines/level3/xgemm.hpp @@ -28,36 +28,36 @@ class Xgemm: public Routine { Xgemm(Queue &queue, EventPointer event, const std::string &name = "GEMM"); // Templated-precision implementation of the routine - StatusCode DoGemm(const Layout layout, const Transpose a_transpose, const Transpose b_transpose, - const size_t m, const size_t n, const size_t k, + void DoGemm(const Layout layout, const Transpose a_transpose, const Transpose b_transpose, + const size_t m, const size_t n, const size_t k, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, + const T beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); + + // Indirect version of GEMM (with pre and post-processing kernels) + void GemmIndirect(const size_t m, const size_t n, const size_t k, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, const T beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); - - // Indirect version of GEMM (with pre and post-processing kernels) - StatusCode GemmIndirect(const size_t m, const size_t n, const size_t k, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, - const T beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld, - const bool a_do_transpose, const bool b_do_transpose, const bool c_do_transpose, - const bool a_conjugate, const bool b_conjugate, - const size_t a_one, const size_t a_two, const bool a_want_rotated, - const size_t b_one, const size_t b_two, const bool b_want_rotated, - const size_t c_one, const size_t c_two, const bool c_want_rotated); + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld, + const bool a_do_transpose, const bool b_do_transpose, const bool c_do_transpose, + const bool a_conjugate, const bool b_conjugate, + const size_t a_one, const size_t a_two, const bool a_want_rotated, + const size_t b_one, const size_t b_two, const bool b_want_rotated, + const size_t c_one, const size_t c_two, const bool c_want_rotated); // Direct version of GEMM (no pre and post-processing kernels) - StatusCode GemmDirect(const size_t m, const size_t n, const size_t k, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, - const T beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld, - const bool a_do_transpose, const bool b_do_transpose, const bool c_do_transpose, - const bool a_conjugate, const bool b_conjugate); + void GemmDirect(const size_t m, const size_t n, const size_t k, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, + const T beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld, + const bool a_do_transpose, const bool b_do_transpose, const bool c_do_transpose, + const bool a_conjugate, const bool b_conjugate); }; // ================================================================================================= diff --git a/src/routines/level3/xhemm.cpp b/src/routines/level3/xhemm.cpp index 9813503e..e5b1502a 100644 --- a/src/routines/level3/xhemm.cpp +++ b/src/routines/level3/xhemm.cpp @@ -29,7 +29,7 @@ Xhemm::Xhemm(Queue &queue, EventPointer event, const std::string &name): // The main routine template -StatusCode Xhemm::DoHemm(const Layout layout, const Side side, const Triangle triangle, +void Xhemm::DoHemm(const Layout layout, const Side side, const Triangle triangle, const size_t m, const size_t n, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, @@ -38,15 +38,14 @@ StatusCode Xhemm::DoHemm(const Layout layout, const Side side, const Triangle const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { // Makes sure all dimensions are larger than zero - if ((m == 0) || (n == 0) ) { return StatusCode::kInvalidDimension; } + if ((m == 0) || (n == 0) ) { throw BLASError(StatusCode::kInvalidDimension); } // Computes the k dimension. This is based on whether or not the hermitian matrix is A (on the // left) or B (on the right) in the Xgemm routine. auto k = (side == Side::kLeft) ? m : n; // Checks for validity of the squared A matrix - auto status = TestMatrixA(k, k, a_buffer, a_offset, a_ld); - if (ErrorIn(status)) { return status; } + TestMatrixA(k, k, a_buffer, a_offset, a_ld); // Determines which kernel to run based on the layout (the Xgemm kernel assumes column-major as // default) and on whether we are dealing with an upper or lower triangle of the hermitian matrix @@ -55,73 +54,68 @@ StatusCode Xhemm::DoHemm(const Layout layout, const Side side, const Triangle auto kernel_name = (is_upper) ? "HermUpperToSquared" : "HermLowerToSquared"; // Temporary buffer for a copy of the hermitian matrix - try { - auto temp_herm = Buffer(context_, k*k); - - // Creates a general matrix from the hermitian matrix to be able to run the regular Xgemm - // routine afterwards + auto temp_herm = Buffer(context_, k*k); + + // Creates a general matrix from the hermitian matrix to be able to run the regular Xgemm + // routine afterwards + const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); + auto kernel = Kernel(program, kernel_name); + + // Sets the arguments for the hermitian-to-squared kernel + kernel.SetArgument(0, static_cast(k)); + kernel.SetArgument(1, static_cast(a_ld)); + kernel.SetArgument(2, static_cast(a_offset)); + kernel.SetArgument(3, a_buffer()); + kernel.SetArgument(4, static_cast(k)); + kernel.SetArgument(5, static_cast(k)); + kernel.SetArgument(6, static_cast(0)); + kernel.SetArgument(7, temp_herm()); + + // Uses the common padding kernel's thread configuration. This is allowed, since the + // hermitian-to-squared kernel uses the same parameters. + auto global = std::vector{Ceil(CeilDiv(k, db_["PAD_WPTX"]), db_["PAD_DIMX"]), + Ceil(CeilDiv(k, db_["PAD_WPTY"]), db_["PAD_DIMY"])}; + auto local = std::vector{db_["PAD_DIMX"], db_["PAD_DIMY"]}; + auto kernelEvent = Event(); + RunKernel(kernel, queue_, device_, global, local, kernelEvent.pointer()); + + // Synchronize now: 'DoGemm' does not accept a list of events to wait for + kernelEvent.WaitForCompletion(); + + // Runs the regular Xgemm code with either "C := AB+C" or ... + if (side == Side::kLeft) { + DoGemm(layout, Transpose::kNo, Transpose::kNo, + m, n, k, + alpha, + temp_herm, 0, k, + b_buffer, b_offset, b_ld, + beta, + c_buffer, c_offset, c_ld); + } + + // ... with "C := BA+C". Note that A and B are now reversed. + else { try { - const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); - auto kernel = Kernel(program, kernel_name); - - // Sets the arguments for the hermitian-to-squared kernel - kernel.SetArgument(0, static_cast(k)); - kernel.SetArgument(1, static_cast(a_ld)); - kernel.SetArgument(2, static_cast(a_offset)); - kernel.SetArgument(3, a_buffer()); - kernel.SetArgument(4, static_cast(k)); - kernel.SetArgument(5, static_cast(k)); - kernel.SetArgument(6, static_cast(0)); - kernel.SetArgument(7, temp_herm()); - - // Uses the common padding kernel's thread configuration. This is allowed, since the - // hermitian-to-squared kernel uses the same parameters. - auto global = std::vector{Ceil(CeilDiv(k, db_["PAD_WPTX"]), db_["PAD_DIMX"]), - Ceil(CeilDiv(k, db_["PAD_WPTY"]), db_["PAD_DIMY"])}; - auto local = std::vector{db_["PAD_DIMX"], db_["PAD_DIMY"]}; - auto kernelEvent = Event(); - status = RunKernel(kernel, queue_, device_, global, local, kernelEvent.pointer()); - if (ErrorIn(status)) { return status; } - - // Synchronize now: 'DoGemm' does not accept a list of events to wait for - kernelEvent.WaitForCompletion(); - - // Runs the regular Xgemm code with either "C := AB+C" or ... - if (side == Side::kLeft) { - status = DoGemm(layout, Transpose::kNo, Transpose::kNo, - m, n, k, - alpha, - temp_herm, 0, k, - b_buffer, b_offset, b_ld, - beta, - c_buffer, c_offset, c_ld); - } - - // ... with "C := BA+C". Note that A and B are now reversed. - else { - status = DoGemm(layout, Transpose::kNo, Transpose::kNo, - m, n, k, - alpha, - b_buffer, b_offset, b_ld, - temp_herm, 0, k, - beta, - c_buffer, c_offset, c_ld); - - // A and B are now reversed, so also reverse the error codes returned from the Xgemm routine - switch(status) { - case StatusCode::kInvalidMatrixA: status = StatusCode::kInvalidMatrixB; break; - case StatusCode::kInvalidMatrixB: status = StatusCode::kInvalidMatrixA; break; - case StatusCode::kInvalidLeadDimA: status = StatusCode::kInvalidLeadDimB; break; - case StatusCode::kInvalidLeadDimB: status = StatusCode::kInvalidLeadDimA; break; - case StatusCode::kInsufficientMemoryA: status = StatusCode::kInsufficientMemoryB; break; - case StatusCode::kInsufficientMemoryB: status = StatusCode::kInsufficientMemoryA; break; - } + DoGemm(layout, Transpose::kNo, Transpose::kNo, + m, n, k, + alpha, + b_buffer, b_offset, b_ld, + temp_herm, 0, k, + beta, + c_buffer, c_offset, c_ld); + } catch (BLASError &e) { + // A and B are now reversed, so also reverse the error codes returned from the Xgemm routine + switch(e.status()) { + case StatusCode::kInvalidMatrixA: throw BLASError(StatusCode::kInvalidMatrixB, e.details()); + case StatusCode::kInvalidMatrixB: throw BLASError(StatusCode::kInvalidMatrixA, e.details()); + case StatusCode::kInvalidLeadDimA: throw BLASError(StatusCode::kInvalidLeadDimB, e.details()); + case StatusCode::kInvalidLeadDimB: throw BLASError(StatusCode::kInvalidLeadDimA, e.details()); + case StatusCode::kInsufficientMemoryA: throw BLASError(StatusCode::kInsufficientMemoryB, e.details()); + case StatusCode::kInsufficientMemoryB: throw BLASError(StatusCode::kInsufficientMemoryA, e.details()); + default: throw; } - - // Return the status of the Xgemm routine - return status; - } catch (...) { return StatusCode::kInvalidKernel; } - } catch (...) { return StatusCode::kTempBufferAllocFailure; } + } + } } // ================================================================================================= diff --git a/src/routines/level3/xhemm.hpp b/src/routines/level3/xhemm.hpp index 272bd2ec..2385706e 100644 --- a/src/routines/level3/xhemm.hpp +++ b/src/routines/level3/xhemm.hpp @@ -37,13 +37,13 @@ class Xhemm: public Xgemm { Xhemm(Queue &queue, EventPointer event, const std::string &name = "HEMM"); // Templated-precision implementation of the routine - StatusCode DoHemm(const Layout layout, const Side side, const Triangle triangle, - const size_t m, const size_t n, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, - const T beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); + void DoHemm(const Layout layout, const Side side, const Triangle triangle, + const size_t m, const size_t n, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, + const T beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); }; // ================================================================================================= diff --git a/src/routines/level3/xher2k.cpp b/src/routines/level3/xher2k.cpp index ba770065..a326dfbe 100644 --- a/src/routines/level3/xher2k.cpp +++ b/src/routines/level3/xher2k.cpp @@ -39,16 +39,16 @@ Xher2k::Xher2k(Queue &queue, EventPointer event, const std::string &name): // The main routine template -StatusCode Xher2k::DoHer2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose, - const size_t n, const size_t k, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, - const U beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { +void Xher2k::DoHer2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose, + const size_t n, const size_t k, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, + const U beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { // Makes sure all dimensions are larger than zero - if ((n == 0) || (k == 0) ) { return StatusCode::kInvalidDimension; } + if ((n == 0) || (k == 0) ) { throw BLASError(StatusCode::kInvalidDimension); } // Determines whether to apply the conjugate transpose to matrix B (argument: no transpose) or // to matrix A (argument: conjugate transpose) @@ -71,12 +71,9 @@ StatusCode Xher2k::DoHer2k(const Layout layout, const Triangle triangle, co // matrix A cannot be less than N when rotated, or less than K when not-rotated // matrix B cannot be less than N when rotated, or less than K when not-rotated // matrix C cannot be less than N - auto status = TestMatrixA(ab_one, ab_two, a_buffer, a_offset, a_ld); - if (ErrorIn(status)) { return status; } - status = TestMatrixB(ab_one, ab_two, b_buffer, b_offset, b_ld); - if (ErrorIn(status)) { return status; } - status = TestMatrixC(n, n, c_buffer, c_offset, c_ld); - if (ErrorIn(status)) { return status; } + TestMatrixA(ab_one, ab_two, a_buffer, a_offset, a_ld); + TestMatrixB(ab_one, ab_two, b_buffer, b_offset, b_ld); + TestMatrixC(n, n, c_buffer, c_offset, c_ld); // Calculates the ceiled versions of n and k auto n_ceiled = Ceil(n, db_["NWG"]); @@ -85,145 +82,128 @@ StatusCode Xher2k::DoHer2k(const Layout layout, const Triangle triangle, co // Decides which kernel to run: the upper-triangular or lower-triangular version auto kernel_name = (triangle == Triangle::kUpper) ? "XgemmUpper" : "XgemmLower"; - // The padded/transposed input/output matrices: if memory allocation fails, throw an exception - try { - - // Loads the program from the database - const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); - - // Determines whether or not temporary matrices are needed - auto a1_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && - ab_rotated == false && ab_conjugate == false; - auto a2_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && - ab_rotated == false && ab_conjugate == true; - auto b1_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 && - ab_rotated == false && ab_conjugate == false; - auto b2_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 && - ab_rotated == false && ab_conjugate == true; - - // Creates the temporary matrices - auto a1_temp = (a1_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto a2_temp = (a2_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto b1_temp = (b1_no_temp) ? b_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto b2_temp = (b2_no_temp) ? b_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto c_temp = Buffer(context_, n_ceiled*n_ceiled); - - // Convert the arguments to complex versions - auto complex_beta = T{beta, static_cast(0.0)}; - - // Events of all kernels (including pre/post processing kernels) - auto eventWaitList = std::vector(); - auto emptyEventList = std::vector(); - - // Runs the pre-processing kernels. This transposes the matrices A and B, but also pads zeros to - // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In - // case nothing has to be done, these kernels can be skipped. - if (!a1_no_temp) { - auto eventProcessA1 = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA1.pointer(), emptyEventList, - ab_one, ab_two, a_ld, a_offset, a_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, a1_temp, - ConstantOne(), program, - true, ab_rotated, ab_conjugate); - eventWaitList.push_back(eventProcessA1); - if (ErrorIn(status)) { return status; } - } - if (!a2_no_temp) { - auto eventProcessA2 = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA2.pointer(), emptyEventList, - ab_one, ab_two, a_ld, a_offset, a_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, a2_temp, - ConstantOne(), program, - true, ab_rotated, !ab_conjugate); - eventWaitList.push_back(eventProcessA2); - if (ErrorIn(status)) { return status; } - } - if (!b1_no_temp) { - auto eventProcessB1 = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB1.pointer(), emptyEventList, - ab_one, ab_two, b_ld, b_offset, b_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, b1_temp, - ConstantOne(), program, - true, ab_rotated, ab_conjugate); - eventWaitList.push_back(eventProcessB1); - if (ErrorIn(status)) { return status; } - } - if (!b2_no_temp) { - auto eventProcessB2 = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB2.pointer(), emptyEventList, - ab_one, ab_two, b_ld, b_offset, b_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, b2_temp, - ConstantOne(), program, - true, ab_rotated, !ab_conjugate); - eventWaitList.push_back(eventProcessB2); - if (ErrorIn(status)) { return status; } - } - - // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to - // modify the other triangle. - auto eventProcessC = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, - n, n, c_ld, c_offset, c_buffer, - n_ceiled, n_ceiled, n_ceiled, 0, c_temp, - ConstantOne(), program, - true, c_rotated, false); - eventWaitList.push_back(eventProcessC); - if (ErrorIn(status)) { return status; } - - // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary - try { - auto kernel = Kernel(program, kernel_name); - - // Sets the kernel arguments - kernel.SetArgument(0, static_cast(n_ceiled)); - kernel.SetArgument(1, static_cast(k_ceiled)); - kernel.SetArgument(2, GetRealArg(alpha)); - kernel.SetArgument(3, GetRealArg(complex_beta)); - kernel.SetArgument(4, a1_temp()); - kernel.SetArgument(5, b2_temp()); - kernel.SetArgument(6, c_temp()); - - // Computes the global and local thread sizes - auto global = std::vector{ - (n_ceiled * db_["MDIMC"]) / db_["MWG"], - (n_ceiled * db_["NDIMC"]) / db_["NWG"] - }; - auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; - - // Launches the kernel - auto eventKernel1 = Event(); - status = RunKernel(kernel, queue_, device_, global, local, eventKernel1.pointer(), eventWaitList); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventKernel1); - - // Swaps the arguments for matrices A and B, sets 'beta' to 1, and conjugate alpha - auto conjugate_alpha = T{alpha.real(), -alpha.imag()}; - auto complex_one = T{static_cast(1.0), static_cast(0.0)}; - kernel.SetArgument(2, GetRealArg(conjugate_alpha)); - kernel.SetArgument(3, GetRealArg(complex_one)); - kernel.SetArgument(4, b1_temp()); - kernel.SetArgument(5, a2_temp()); - - // Runs the kernel again - auto eventKernel2 = Event(); - status = RunKernel(kernel, queue_, device_, global, local, eventKernel2.pointer(), eventWaitList); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventKernel2); - - // Runs the post-processing kernel - auto upper = (triangle == Triangle::kUpper); - auto lower = (triangle == Triangle::kLower); - status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, - n_ceiled, n_ceiled, n_ceiled, 0, c_temp, - n, n, c_ld, c_offset, c_buffer, - ConstantOne(), program, - false, c_rotated, false, upper, lower, true); - if (ErrorIn(status)) { return status; } - - // Successfully finished the computation - return StatusCode::kSuccess; - } catch (...) { return StatusCode::kInvalidKernel; } - } catch (...) { return StatusCode::kTempBufferAllocFailure; } + // Loads the program from the database + const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); + + // Determines whether or not temporary matrices are needed + auto a1_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && + ab_rotated == false && ab_conjugate == false; + auto a2_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && + ab_rotated == false && ab_conjugate == true; + auto b1_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 && + ab_rotated == false && ab_conjugate == false; + auto b2_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 && + ab_rotated == false && ab_conjugate == true; + + // Creates the temporary matrices + auto a1_temp = (a1_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto a2_temp = (a2_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto b1_temp = (b1_no_temp) ? b_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto b2_temp = (b2_no_temp) ? b_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto c_temp = Buffer(context_, n_ceiled*n_ceiled); + + // Convert the arguments to complex versions + auto complex_beta = T{beta, static_cast(0.0)}; + + // Events of all kernels (including pre/post processing kernels) + auto eventWaitList = std::vector(); + auto emptyEventList = std::vector(); + + // Runs the pre-processing kernels. This transposes the matrices A and B, but also pads zeros to + // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In + // case nothing has to be done, these kernels can be skipped. + if (!a1_no_temp) { + auto eventProcessA1 = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA1.pointer(), emptyEventList, + ab_one, ab_two, a_ld, a_offset, a_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, a1_temp, + ConstantOne(), program, + true, ab_rotated, ab_conjugate); + eventWaitList.push_back(eventProcessA1); + } + if (!a2_no_temp) { + auto eventProcessA2 = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA2.pointer(), emptyEventList, + ab_one, ab_two, a_ld, a_offset, a_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, a2_temp, + ConstantOne(), program, + true, ab_rotated, !ab_conjugate); + eventWaitList.push_back(eventProcessA2); + } + if (!b1_no_temp) { + auto eventProcessB1 = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB1.pointer(), emptyEventList, + ab_one, ab_two, b_ld, b_offset, b_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, b1_temp, + ConstantOne(), program, + true, ab_rotated, ab_conjugate); + eventWaitList.push_back(eventProcessB1); + } + if (!b2_no_temp) { + auto eventProcessB2 = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB2.pointer(), emptyEventList, + ab_one, ab_two, b_ld, b_offset, b_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, b2_temp, + ConstantOne(), program, + true, ab_rotated, !ab_conjugate); + eventWaitList.push_back(eventProcessB2); + } + + // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to + // modify the other triangle. + auto eventProcessC = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, + n, n, c_ld, c_offset, c_buffer, + n_ceiled, n_ceiled, n_ceiled, 0, c_temp, + ConstantOne(), program, + true, c_rotated, false); + eventWaitList.push_back(eventProcessC); + + // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary + auto kernel = Kernel(program, kernel_name); + + // Sets the kernel arguments + kernel.SetArgument(0, static_cast(n_ceiled)); + kernel.SetArgument(1, static_cast(k_ceiled)); + kernel.SetArgument(2, GetRealArg(alpha)); + kernel.SetArgument(3, GetRealArg(complex_beta)); + kernel.SetArgument(4, a1_temp()); + kernel.SetArgument(5, b2_temp()); + kernel.SetArgument(6, c_temp()); + + // Computes the global and local thread sizes + auto global = std::vector{ + (n_ceiled * db_["MDIMC"]) / db_["MWG"], + (n_ceiled * db_["NDIMC"]) / db_["NWG"] + }; + auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; + + // Launches the kernel + auto eventKernel1 = Event(); + RunKernel(kernel, queue_, device_, global, local, eventKernel1.pointer(), eventWaitList); + eventWaitList.push_back(eventKernel1); + + // Swaps the arguments for matrices A and B, sets 'beta' to 1, and conjugate alpha + auto conjugate_alpha = T{alpha.real(), -alpha.imag()}; + auto complex_one = T{static_cast(1.0), static_cast(0.0)}; + kernel.SetArgument(2, GetRealArg(conjugate_alpha)); + kernel.SetArgument(3, GetRealArg(complex_one)); + kernel.SetArgument(4, b1_temp()); + kernel.SetArgument(5, a2_temp()); + + // Runs the kernel again + auto eventKernel2 = Event(); + RunKernel(kernel, queue_, device_, global, local, eventKernel2.pointer(), eventWaitList); + eventWaitList.push_back(eventKernel2); + + // Runs the post-processing kernel + auto upper = (triangle == Triangle::kUpper); + auto lower = (triangle == Triangle::kLower); + PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, + n_ceiled, n_ceiled, n_ceiled, 0, c_temp, + n, n, c_ld, c_offset, c_buffer, + ConstantOne(), program, + false, c_rotated, false, upper, lower, true); } // ================================================================================================= diff --git a/src/routines/level3/xher2k.hpp b/src/routines/level3/xher2k.hpp index 23996219..acc346e4 100644 --- a/src/routines/level3/xher2k.hpp +++ b/src/routines/level3/xher2k.hpp @@ -30,13 +30,13 @@ class Xher2k: public Routine { Xher2k(Queue &queue, EventPointer event, const std::string &name = "HER2K"); // Templated-precision implementation of the routine - StatusCode DoHer2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose, - const size_t n, const size_t k, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, - const U beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); + void DoHer2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose, + const size_t n, const size_t k, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, + const U beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); }; // ================================================================================================= diff --git a/src/routines/level3/xherk.cpp b/src/routines/level3/xherk.cpp index 3063f3bc..6e36714e 100644 --- a/src/routines/level3/xherk.cpp +++ b/src/routines/level3/xherk.cpp @@ -39,7 +39,7 @@ Xherk::Xherk(Queue &queue, EventPointer event, const std::string &name): // The main routine template -StatusCode Xherk::DoHerk(const Layout layout, const Triangle triangle, const Transpose a_transpose, +void Xherk::DoHerk(const Layout layout, const Triangle triangle, const Transpose a_transpose, const size_t n, const size_t k, const U alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, @@ -47,7 +47,7 @@ StatusCode Xherk::DoHerk(const Layout layout, const Triangle triangle, cons const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { // Makes sure all dimensions are larger than zero - if ((n == 0) || (k == 0) ) { return StatusCode::kInvalidDimension; } + if ((n == 0) || (k == 0) ) { throw BLASError(StatusCode::kInvalidDimension); } // Determines whether to apply the conjugate transpose to matrix B (argument: no transpose) or // to matrix A (argument: conjugate transpose) @@ -70,10 +70,8 @@ StatusCode Xherk::DoHerk(const Layout layout, const Triangle triangle, cons // space. Also tests that the leading dimensions of: // matrix A cannot be less than N when rotated, or less than K when not-rotated // matrix C cannot be less than N - auto status = TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); - if (ErrorIn(status)) { return status; } - status = TestMatrixC(n, n, c_buffer, c_offset, c_ld); - if (ErrorIn(status)) { return status; } + TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); + TestMatrixC(n, n, c_buffer, c_offset, c_ld); // Calculates the ceiled versions of n and k auto n_ceiled = Ceil(n, db_["NWG"]); @@ -82,106 +80,92 @@ StatusCode Xherk::DoHerk(const Layout layout, const Triangle triangle, cons // Decides which kernel to run: the upper-triangular or lower-triangular version auto kernel_name = (triangle == Triangle::kUpper) ? "XgemmUpper" : "XgemmLower"; - // The padded/transposed input/output matrices: if memory allocation fails, throw an exception - try { - - // Loads the program from the database - const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); - - // Determines whether or not temporary matrices are needed - auto a_no_temp = a_one == n_ceiled && a_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && - a_rotated == false && a_conjugate == false; - auto b_no_temp = a_one == n_ceiled && a_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && - a_rotated == false && b_conjugate == false; - - // Creates the temporary matrices - auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto b_temp = (b_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto c_temp = Buffer(context_, n_ceiled*n_ceiled); - - // Convert the arguments to complex versions - auto complex_alpha = T{alpha, static_cast(0.0)}; - auto complex_beta = T{beta, static_cast(0.0)}; - - // Events of all kernels (including pre/post processing kernels) - auto eventWaitList = std::vector(); - auto emptyEventList = std::vector(); - - // Runs the pre-processing kernel for matrix A. This transposes the matrix, but also pads zeros - // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In - // case nothing has to be done, these kernels can be skipped. Two copies are created. - if (!a_no_temp) { - auto eventProcessA = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, - a_one, a_two, a_ld, a_offset, a_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, a_temp, - ConstantOne(), program, - true, a_rotated, a_conjugate); - eventWaitList.push_back(eventProcessA); - if (ErrorIn(status)) { return status; } - } - if (!b_no_temp) { - auto eventProcessB = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList, - a_one, a_two, a_ld, a_offset, a_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, b_temp, - ConstantOne(), program, - true, a_rotated, b_conjugate); - eventWaitList.push_back(eventProcessB); - if (ErrorIn(status)) { return status; } - } - - // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to - // modify the other triangle. - auto eventProcessC = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, - n, n, c_ld, c_offset, c_buffer, - n_ceiled, n_ceiled, n_ceiled, 0, c_temp, - ConstantOne(), program, - true, c_rotated, false); - eventWaitList.push_back(eventProcessC); - if (ErrorIn(status)) { return status; } - - // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary - try { - auto kernel = Kernel(program, kernel_name); - - // Sets the kernel arguments - kernel.SetArgument(0, static_cast(n_ceiled)); - kernel.SetArgument(1, static_cast(k_ceiled)); - kernel.SetArgument(2, GetRealArg(complex_alpha)); - kernel.SetArgument(3, GetRealArg(complex_beta)); - kernel.SetArgument(4, a_temp()); - kernel.SetArgument(5, b_temp()); - kernel.SetArgument(6, c_temp()); - - // Computes the global and local thread sizes - auto global = std::vector{ - (n_ceiled * db_["MDIMC"]) / db_["MWG"], - (n_ceiled * db_["NDIMC"]) / db_["NWG"] - }; - auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; - - // Launches the kernel - auto eventKernel = Event(); - status = RunKernel(kernel, queue_, device_, global, local, eventKernel.pointer(), eventWaitList); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventKernel); - - // Runs the post-processing kernel - auto upper = (triangle == Triangle::kUpper); - auto lower = (triangle == Triangle::kLower); - status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, - n_ceiled, n_ceiled, n_ceiled, 0, c_temp, - n, n, c_ld, c_offset, c_buffer, - ConstantOne(), program, - false, c_rotated, false, upper, lower, true); - if (ErrorIn(status)) { return status; } - - // Successfully finished the computation - return StatusCode::kSuccess; - } catch (...) { return StatusCode::kInvalidKernel; } - } catch (...) { return StatusCode::kTempBufferAllocFailure; } + // Loads the program from the database + const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); + + // Determines whether or not temporary matrices are needed + auto a_no_temp = a_one == n_ceiled && a_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && + a_rotated == false && a_conjugate == false; + auto b_no_temp = a_one == n_ceiled && a_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && + a_rotated == false && b_conjugate == false; + + // Creates the temporary matrices + auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto b_temp = (b_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto c_temp = Buffer(context_, n_ceiled*n_ceiled); + + // Convert the arguments to complex versions + auto complex_alpha = T{alpha, static_cast(0.0)}; + auto complex_beta = T{beta, static_cast(0.0)}; + + // Events of all kernels (including pre/post processing kernels) + auto eventWaitList = std::vector(); + auto emptyEventList = std::vector(); + + // Runs the pre-processing kernel for matrix A. This transposes the matrix, but also pads zeros + // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In + // case nothing has to be done, these kernels can be skipped. Two copies are created. + if (!a_no_temp) { + auto eventProcessA = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, + a_one, a_two, a_ld, a_offset, a_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, a_temp, + ConstantOne(), program, + true, a_rotated, a_conjugate); + eventWaitList.push_back(eventProcessA); + } + if (!b_no_temp) { + auto eventProcessB = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList, + a_one, a_two, a_ld, a_offset, a_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, b_temp, + ConstantOne(), program, + true, a_rotated, b_conjugate); + eventWaitList.push_back(eventProcessB); + } + + // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to + // modify the other triangle. + auto eventProcessC = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, + n, n, c_ld, c_offset, c_buffer, + n_ceiled, n_ceiled, n_ceiled, 0, c_temp, + ConstantOne(), program, + true, c_rotated, false); + eventWaitList.push_back(eventProcessC); + + // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary + auto kernel = Kernel(program, kernel_name); + + // Sets the kernel arguments + kernel.SetArgument(0, static_cast(n_ceiled)); + kernel.SetArgument(1, static_cast(k_ceiled)); + kernel.SetArgument(2, GetRealArg(complex_alpha)); + kernel.SetArgument(3, GetRealArg(complex_beta)); + kernel.SetArgument(4, a_temp()); + kernel.SetArgument(5, b_temp()); + kernel.SetArgument(6, c_temp()); + + // Computes the global and local thread sizes + auto global = std::vector{ + (n_ceiled * db_["MDIMC"]) / db_["MWG"], + (n_ceiled * db_["NDIMC"]) / db_["NWG"] + }; + auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; + + // Launches the kernel + auto eventKernel = Event(); + RunKernel(kernel, queue_, device_, global, local, eventKernel.pointer(), eventWaitList); + eventWaitList.push_back(eventKernel); + + // Runs the post-processing kernel + auto upper = (triangle == Triangle::kUpper); + auto lower = (triangle == Triangle::kLower); + PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, + n_ceiled, n_ceiled, n_ceiled, 0, c_temp, + n, n, c_ld, c_offset, c_buffer, + ConstantOne(), program, + false, c_rotated, false, upper, lower, true); } // ================================================================================================= diff --git a/src/routines/level3/xherk.hpp b/src/routines/level3/xherk.hpp index 3f156a1b..51f29d7e 100644 --- a/src/routines/level3/xherk.hpp +++ b/src/routines/level3/xherk.hpp @@ -30,12 +30,12 @@ class Xherk: public Routine { Xherk(Queue &queue, EventPointer event, const std::string &name = "HERK"); // Templated-precision implementation of the routine - StatusCode DoHerk(const Layout layout, const Triangle triangle, const Transpose a_transpose, - const size_t n, const size_t k, - const U alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const U beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); + void DoHerk(const Layout layout, const Triangle triangle, const Transpose a_transpose, + const size_t n, const size_t k, + const U alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const U beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); }; // ================================================================================================= diff --git a/src/routines/level3/xsymm.cpp b/src/routines/level3/xsymm.cpp index 04e4b718..d7f771d1 100644 --- a/src/routines/level3/xsymm.cpp +++ b/src/routines/level3/xsymm.cpp @@ -29,7 +29,7 @@ Xsymm::Xsymm(Queue &queue, EventPointer event, const std::string &name): // The main routine template -StatusCode Xsymm::DoSymm(const Layout layout, const Side side, const Triangle triangle, +void Xsymm::DoSymm(const Layout layout, const Side side, const Triangle triangle, const size_t m, const size_t n, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, @@ -38,15 +38,14 @@ StatusCode Xsymm::DoSymm(const Layout layout, const Side side, const Triangle const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { // Makes sure all dimensions are larger than zero - if ((m == 0) || (n == 0) ) { return StatusCode::kInvalidDimension; } + if ((m == 0) || (n == 0) ) { throw BLASError(StatusCode::kInvalidDimension); } // Computes the k dimension. This is based on whether or not the symmetric matrix is A (on the // left) or B (on the right) in the Xgemm routine. auto k = (side == Side::kLeft) ? m : n; // Checks for validity of the squared A matrix - auto status = TestMatrixA(k, k, a_buffer, a_offset, a_ld); - if (ErrorIn(status)) { return status; } + TestMatrixA(k, k, a_buffer, a_offset, a_ld); // Determines which kernel to run based on the layout (the Xgemm kernel assumes column-major as // default) and on whether we are dealing with an upper or lower triangle of the symmetric matrix @@ -55,73 +54,68 @@ StatusCode Xsymm::DoSymm(const Layout layout, const Side side, const Triangle auto kernel_name = (is_upper) ? "SymmUpperToSquared" : "SymmLowerToSquared"; // Temporary buffer for a copy of the symmetric matrix - try { - auto temp_symm = Buffer(context_, k*k); - - // Creates a general matrix from the symmetric matrix to be able to run the regular Xgemm - // routine afterwards + auto temp_symm = Buffer(context_, k*k); + + // Creates a general matrix from the symmetric matrix to be able to run the regular Xgemm + // routine afterwards + const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); + auto kernel = Kernel(program, kernel_name); + + // Sets the arguments for the symmetric-to-squared kernel + kernel.SetArgument(0, static_cast(k)); + kernel.SetArgument(1, static_cast(a_ld)); + kernel.SetArgument(2, static_cast(a_offset)); + kernel.SetArgument(3, a_buffer()); + kernel.SetArgument(4, static_cast(k)); + kernel.SetArgument(5, static_cast(k)); + kernel.SetArgument(6, static_cast(0)); + kernel.SetArgument(7, temp_symm()); + + // Uses the common padding kernel's thread configuration. This is allowed, since the + // symmetric-to-squared kernel uses the same parameters. + auto global = std::vector{Ceil(CeilDiv(k, db_["PAD_WPTX"]), db_["PAD_DIMX"]), + Ceil(CeilDiv(k, db_["PAD_WPTY"]), db_["PAD_DIMY"])}; + auto local = std::vector{db_["PAD_DIMX"], db_["PAD_DIMY"]}; + auto kernelEvent = Event(); + RunKernel(kernel, queue_, device_, global, local, kernelEvent.pointer()); + + // Synchronize now: 'DoGemm' does not accept a list of events to wait for + kernelEvent.WaitForCompletion(); + + // Runs the regular Xgemm code with either "C := AB+C" or ... + if (side == Side::kLeft) { + DoGemm(layout, Transpose::kNo, Transpose::kNo, + m, n, k, + alpha, + temp_symm, 0, k, + b_buffer, b_offset, b_ld, + beta, + c_buffer, c_offset, c_ld); + } + + // ... with "C := BA+C". Note that A and B are now reversed. + else { try { - const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); - auto kernel = Kernel(program, kernel_name); - - // Sets the arguments for the symmetric-to-squared kernel - kernel.SetArgument(0, static_cast(k)); - kernel.SetArgument(1, static_cast(a_ld)); - kernel.SetArgument(2, static_cast(a_offset)); - kernel.SetArgument(3, a_buffer()); - kernel.SetArgument(4, static_cast(k)); - kernel.SetArgument(5, static_cast(k)); - kernel.SetArgument(6, static_cast(0)); - kernel.SetArgument(7, temp_symm()); - - // Uses the common padding kernel's thread configuration. This is allowed, since the - // symmetric-to-squared kernel uses the same parameters. - auto global = std::vector{Ceil(CeilDiv(k, db_["PAD_WPTX"]), db_["PAD_DIMX"]), - Ceil(CeilDiv(k, db_["PAD_WPTY"]), db_["PAD_DIMY"])}; - auto local = std::vector{db_["PAD_DIMX"], db_["PAD_DIMY"]}; - auto kernelEvent = Event(); - status = RunKernel(kernel, queue_, device_, global, local, kernelEvent.pointer()); - if (ErrorIn(status)) { return status; } - - // Synchronize now: 'DoGemm' does not accept a list of events to wait for - kernelEvent.WaitForCompletion(); - - // Runs the regular Xgemm code with either "C := AB+C" or ... - if (side == Side::kLeft) { - status = DoGemm(layout, Transpose::kNo, Transpose::kNo, - m, n, k, - alpha, - temp_symm, 0, k, - b_buffer, b_offset, b_ld, - beta, - c_buffer, c_offset, c_ld); - } - - // ... with "C := BA+C". Note that A and B are now reversed. - else { - status = DoGemm(layout, Transpose::kNo, Transpose::kNo, - m, n, k, - alpha, - b_buffer, b_offset, b_ld, - temp_symm, 0, k, - beta, - c_buffer, c_offset, c_ld); - - // A and B are now reversed, so also reverse the error codes returned from the Xgemm routine - switch(status) { - case StatusCode::kInvalidMatrixA: status = StatusCode::kInvalidMatrixB; break; - case StatusCode::kInvalidMatrixB: status = StatusCode::kInvalidMatrixA; break; - case StatusCode::kInvalidLeadDimA: status = StatusCode::kInvalidLeadDimB; break; - case StatusCode::kInvalidLeadDimB: status = StatusCode::kInvalidLeadDimA; break; - case StatusCode::kInsufficientMemoryA: status = StatusCode::kInsufficientMemoryB; break; - case StatusCode::kInsufficientMemoryB: status = StatusCode::kInsufficientMemoryA; break; - } + DoGemm(layout, Transpose::kNo, Transpose::kNo, + m, n, k, + alpha, + b_buffer, b_offset, b_ld, + temp_symm, 0, k, + beta, + c_buffer, c_offset, c_ld); + } catch (BLASError &e) { + // A and B are now reversed, so also reverse the error codes returned from the Xgemm routine + switch(e.status()) { + case StatusCode::kInvalidMatrixA: throw BLASError(StatusCode::kInvalidMatrixB, e.details()); + case StatusCode::kInvalidMatrixB: throw BLASError(StatusCode::kInvalidMatrixA, e.details()); + case StatusCode::kInvalidLeadDimA: throw BLASError(StatusCode::kInvalidLeadDimB, e.details()); + case StatusCode::kInvalidLeadDimB: throw BLASError(StatusCode::kInvalidLeadDimA, e.details()); + case StatusCode::kInsufficientMemoryA: throw BLASError(StatusCode::kInsufficientMemoryB, e.details()); + case StatusCode::kInsufficientMemoryB: throw BLASError(StatusCode::kInsufficientMemoryA, e.details()); + default: throw; } - - // Return the status of the Xgemm routine - return status; - } catch (...) { return StatusCode::kInvalidKernel; } - } catch (...) { return StatusCode::kTempBufferAllocFailure; } + } + } } // ================================================================================================= diff --git a/src/routines/level3/xsymm.hpp b/src/routines/level3/xsymm.hpp index 428f78ef..ee965364 100644 --- a/src/routines/level3/xsymm.hpp +++ b/src/routines/level3/xsymm.hpp @@ -39,13 +39,13 @@ class Xsymm: public Xgemm { Xsymm(Queue &queue, EventPointer event, const std::string &name = "SYMM"); // Templated-precision implementation of the routine - StatusCode DoSymm(const Layout layout, const Side side, const Triangle triangle, - const size_t m, const size_t n, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, - const T beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); + void DoSymm(const Layout layout, const Side side, const Triangle triangle, + const size_t m, const size_t n, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, + const T beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); }; // ================================================================================================= diff --git a/src/routines/level3/xsyr2k.cpp b/src/routines/level3/xsyr2k.cpp index 158cd9e5..b10ee586 100644 --- a/src/routines/level3/xsyr2k.cpp +++ b/src/routines/level3/xsyr2k.cpp @@ -39,7 +39,7 @@ Xsyr2k::Xsyr2k(Queue &queue, EventPointer event, const std::string &name): // The main routine template -StatusCode Xsyr2k::DoSyr2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose, +void Xsyr2k::DoSyr2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose, const size_t n, const size_t k, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, @@ -48,7 +48,7 @@ StatusCode Xsyr2k::DoSyr2k(const Layout layout, const Triangle triangle, cons const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { // Makes sure all dimensions are larger than zero - if ((n == 0) || (k == 0) ) { return StatusCode::kInvalidDimension; } + if ((n == 0) || (k == 0) ) { throw BLASError(StatusCode::kInvalidDimension); } // Computes whether or not the matrices are transposed in memory. This is based on their layout // (row or column-major) and whether or not they are requested to be pre-transposed. @@ -67,12 +67,9 @@ StatusCode Xsyr2k::DoSyr2k(const Layout layout, const Triangle triangle, cons // matrix A cannot be less than N when rotated, or less than K when not-rotated // matrix B cannot be less than N when rotated, or less than K when not-rotated // matrix C cannot be less than N - auto status = TestMatrixA(ab_one, ab_two, a_buffer, a_offset, a_ld); - if (ErrorIn(status)) { return status; } - status = TestMatrixB(ab_one, ab_two, b_buffer, b_offset, b_ld); - if (ErrorIn(status)) { return status; } - status = TestMatrixC(n, n, c_buffer, c_offset, c_ld); - if (ErrorIn(status)) { return status; } + TestMatrixA(ab_one, ab_two, a_buffer, a_offset, a_ld); + TestMatrixB(ab_one, ab_two, b_buffer, b_offset, b_ld); + TestMatrixC(n, n, c_buffer, c_offset, c_ld); // Calculates the ceiled versions of n and k auto n_ceiled = Ceil(n, db_["NWG"]); @@ -81,114 +78,99 @@ StatusCode Xsyr2k::DoSyr2k(const Layout layout, const Triangle triangle, cons // Decides which kernel to run: the upper-triangular or lower-triangular version auto kernel_name = (triangle == Triangle::kUpper) ? "XgemmUpper" : "XgemmLower"; - // The padded/transposed input/output matrices: if memory allocation fails, throw an exception - try { - - // Loads the program from the database - const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); - - // Determines whether or not temporary matrices are needed - auto a_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && - ab_rotated == false; - auto b_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 && - ab_rotated == false; - - // Creates the temporary matrices - auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto b_temp = (b_no_temp) ? b_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto c_temp = Buffer(context_, n_ceiled*n_ceiled); - - // Events of all kernels (including pre/post processing kernels) - auto eventWaitList = std::vector(); - auto emptyEventList = std::vector(); - - // Runs the pre-processing kernels. This transposes the matrices A and B, but also pads zeros to - // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In - // case nothing has to be done, these kernels can be skipped. - if (!a_no_temp) { - auto eventProcessA = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, - ab_one, ab_two, a_ld, a_offset, a_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, a_temp, - ConstantOne(), program, - true, ab_rotated, false); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventProcessA); - } - if (!b_no_temp) { - auto eventProcessB = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList, - ab_one, ab_two, b_ld, b_offset, b_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, b_temp, - ConstantOne(), program, - true, ab_rotated, false); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventProcessB); - } - - // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to - // modify the other triangle. - auto eventProcessC = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, - n, n, c_ld, c_offset, c_buffer, - n_ceiled, n_ceiled, n_ceiled, 0, c_temp, - ConstantOne(), program, - true, c_rotated, false); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventProcessC); - - // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary - try { - auto kernel = Kernel(program, kernel_name); - - // Sets the kernel arguments - kernel.SetArgument(0, static_cast(n_ceiled)); - kernel.SetArgument(1, static_cast(k_ceiled)); - kernel.SetArgument(2, GetRealArg(alpha)); - kernel.SetArgument(3, GetRealArg(beta)); - kernel.SetArgument(4, a_temp()); - kernel.SetArgument(5, b_temp()); - kernel.SetArgument(6, c_temp()); - - // Computes the global and local thread sizes - auto global = std::vector{ - (n_ceiled * db_["MDIMC"]) / db_["MWG"], - (n_ceiled * db_["NDIMC"]) / db_["NWG"] - }; - auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; - - // Launches the kernel - auto eventKernel1 = Event(); - status = RunKernel(kernel, queue_, device_, global, local, eventKernel1.pointer(), eventWaitList); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventKernel1); - - // Swaps the arguments for matrices A and B, and sets 'beta' to 1 - auto one = static_cast(1); - kernel.SetArgument(3, GetRealArg(one)); - kernel.SetArgument(4, b_temp()); - kernel.SetArgument(5, a_temp()); - - // Runs the kernel again - auto eventKernel2 = Event(); - status = RunKernel(kernel, queue_, device_, global, local, eventKernel2.pointer(), eventWaitList); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventKernel2); - - // Runs the post-processing kernel - auto upper = (triangle == Triangle::kUpper); - auto lower = (triangle == Triangle::kLower); - status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, - n_ceiled, n_ceiled, n_ceiled, 0, c_temp, - n, n, c_ld, c_offset, c_buffer, - ConstantOne(), program, - false, c_rotated, false, upper, lower, false); - if (ErrorIn(status)) { return status; } - - // Successfully finished the computation - return StatusCode::kSuccess; - } catch (...) { return StatusCode::kInvalidKernel; } - } catch (...) { return StatusCode::kTempBufferAllocFailure; } + // Loads the program from the database + const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); + + // Determines whether or not temporary matrices are needed + auto a_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && + ab_rotated == false; + auto b_no_temp = ab_one == n_ceiled && ab_two == k_ceiled && b_ld == n_ceiled && b_offset == 0 && + ab_rotated == false; + + // Creates the temporary matrices + auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto b_temp = (b_no_temp) ? b_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto c_temp = Buffer(context_, n_ceiled*n_ceiled); + + // Events of all kernels (including pre/post processing kernels) + auto eventWaitList = std::vector(); + auto emptyEventList = std::vector(); + + // Runs the pre-processing kernels. This transposes the matrices A and B, but also pads zeros to + // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In + // case nothing has to be done, these kernels can be skipped. + if (!a_no_temp) { + auto eventProcessA = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, + ab_one, ab_two, a_ld, a_offset, a_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, a_temp, + ConstantOne(), program, + true, ab_rotated, false); + eventWaitList.push_back(eventProcessA); + } + if (!b_no_temp) { + auto eventProcessB = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessB.pointer(), emptyEventList, + ab_one, ab_two, b_ld, b_offset, b_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, b_temp, + ConstantOne(), program, + true, ab_rotated, false); + eventWaitList.push_back(eventProcessB); + } + + // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to + // modify the other triangle. + auto eventProcessC = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, + n, n, c_ld, c_offset, c_buffer, + n_ceiled, n_ceiled, n_ceiled, 0, c_temp, + ConstantOne(), program, + true, c_rotated, false); + eventWaitList.push_back(eventProcessC); + + // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary + auto kernel = Kernel(program, kernel_name); + + // Sets the kernel arguments + kernel.SetArgument(0, static_cast(n_ceiled)); + kernel.SetArgument(1, static_cast(k_ceiled)); + kernel.SetArgument(2, GetRealArg(alpha)); + kernel.SetArgument(3, GetRealArg(beta)); + kernel.SetArgument(4, a_temp()); + kernel.SetArgument(5, b_temp()); + kernel.SetArgument(6, c_temp()); + + // Computes the global and local thread sizes + auto global = std::vector{ + (n_ceiled * db_["MDIMC"]) / db_["MWG"], + (n_ceiled * db_["NDIMC"]) / db_["NWG"] + }; + auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; + + // Launches the kernel + auto eventKernel1 = Event(); + RunKernel(kernel, queue_, device_, global, local, eventKernel1.pointer(), eventWaitList); + eventWaitList.push_back(eventKernel1); + + // Swaps the arguments for matrices A and B, and sets 'beta' to 1 + auto one = static_cast(1); + kernel.SetArgument(3, GetRealArg(one)); + kernel.SetArgument(4, b_temp()); + kernel.SetArgument(5, a_temp()); + + // Runs the kernel again + auto eventKernel2 = Event(); + RunKernel(kernel, queue_, device_, global, local, eventKernel2.pointer(), eventWaitList); + eventWaitList.push_back(eventKernel2); + + // Runs the post-processing kernel + auto upper = (triangle == Triangle::kUpper); + auto lower = (triangle == Triangle::kLower); + PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, + n_ceiled, n_ceiled, n_ceiled, 0, c_temp, + n, n, c_ld, c_offset, c_buffer, + ConstantOne(), program, + false, c_rotated, false, upper, lower, false); } // ================================================================================================= diff --git a/src/routines/level3/xsyr2k.hpp b/src/routines/level3/xsyr2k.hpp index 56185653..a02c6e16 100644 --- a/src/routines/level3/xsyr2k.hpp +++ b/src/routines/level3/xsyr2k.hpp @@ -30,13 +30,13 @@ class Xsyr2k: public Routine { Xsyr2k(Queue &queue, EventPointer event, const std::string &name = "SYR2K"); // Templated-precision implementation of the routine - StatusCode DoSyr2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose, - const size_t n, const size_t k, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, - const T beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); + void DoSyr2k(const Layout layout, const Triangle triangle, const Transpose ab_transpose, + const size_t n, const size_t k, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld, + const T beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); }; // ================================================================================================= diff --git a/src/routines/level3/xsyrk.cpp b/src/routines/level3/xsyrk.cpp index e1a72ef6..93fd4666 100644 --- a/src/routines/level3/xsyrk.cpp +++ b/src/routines/level3/xsyrk.cpp @@ -39,7 +39,7 @@ Xsyrk::Xsyrk(Queue &queue, EventPointer event, const std::string &name): // The main routine template -StatusCode Xsyrk::DoSyrk(const Layout layout, const Triangle triangle, const Transpose a_transpose, +void Xsyrk::DoSyrk(const Layout layout, const Triangle triangle, const Transpose a_transpose, const size_t n, const size_t k, const T alpha, const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, @@ -47,7 +47,7 @@ StatusCode Xsyrk::DoSyrk(const Layout layout, const Triangle triangle, const const Buffer &c_buffer, const size_t c_offset, const size_t c_ld) { // Makes sure all dimensions are larger than zero - if ((n == 0) || (k == 0) ) { return StatusCode::kInvalidDimension; } + if ((n == 0) || (k == 0) ) { throw BLASError(StatusCode::kInvalidDimension); } // Computes whether or not the matrices are transposed in memory. This is based on their layout // (row or column-major) and whether or not they are requested to be pre-transposed. @@ -65,10 +65,8 @@ StatusCode Xsyrk::DoSyrk(const Layout layout, const Triangle triangle, const // space. Also tests that the leading dimensions of: // matrix A cannot be less than N when rotated, or less than K when not-rotated // matrix C cannot be less than N - auto status = TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); - if (ErrorIn(status)) { return status; } - status = TestMatrixC(n, n, c_buffer, c_offset, c_ld); - if (ErrorIn(status)) { return status; } + TestMatrixA(a_one, a_two, a_buffer, a_offset, a_ld); + TestMatrixC(n, n, c_buffer, c_offset, c_ld); // Calculates the ceiled versions of n and k auto n_ceiled = Ceil(n, db_["NWG"]); @@ -77,90 +75,76 @@ StatusCode Xsyrk::DoSyrk(const Layout layout, const Triangle triangle, const // Decides which kernel to run: the upper-triangular or lower-triangular version auto kernel_name = (triangle == Triangle::kUpper) ? "XgemmUpper" : "XgemmLower"; - // The padded/transposed input/output matrices: if memory allocation fails, throw an exception - try { - - // Loads the program from the database - const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); - - // Determines whether or not temporary matrices are needed - auto a_no_temp = a_one == n_ceiled && a_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && - a_rotated == false; - - // Creates the temporary matrices - auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); - auto c_temp = Buffer(context_, n_ceiled*n_ceiled); - - // Events of all kernels (including pre/post processing kernels) - auto eventWaitList = std::vector(); - auto emptyEventList = std::vector(); - - // Runs the pre-processing kernel for matrix A. This transposes the matrix, but also pads zeros - // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In - // case nothing has to be done, these kernels can be skipped. - if (!a_no_temp) { - auto eventProcessA = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, - a_one, a_two, a_ld, a_offset, a_buffer, - n_ceiled, k_ceiled, n_ceiled, 0, a_temp, - ConstantOne(), program, - true, a_rotated, false); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventProcessA); - } - - // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to - // modify the other triangle. - auto eventProcessC = Event(); - status = PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, - n, n, c_ld, c_offset, c_buffer, - n_ceiled, n_ceiled, n_ceiled, 0, c_temp, - ConstantOne(), program, - true, c_rotated, false); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventProcessC); - - // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary - try { - auto kernel = Kernel(program, kernel_name); - - // Sets the kernel arguments - kernel.SetArgument(0, static_cast(n_ceiled)); - kernel.SetArgument(1, static_cast(k_ceiled)); - kernel.SetArgument(2, GetRealArg(alpha)); - kernel.SetArgument(3, GetRealArg(beta)); - kernel.SetArgument(4, a_temp()); - kernel.SetArgument(5, a_temp()); - kernel.SetArgument(6, c_temp()); - - // Computes the global and local thread sizes - auto global = std::vector{ - (n_ceiled * db_["MDIMC"]) / db_["MWG"], - (n_ceiled * db_["NDIMC"]) / db_["NWG"] - }; - auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; - - // Launches the kernel - auto eventKernel = Event(); - status = RunKernel(kernel, queue_, device_, global, local, eventKernel.pointer(), eventWaitList); - if (ErrorIn(status)) { return status; } - eventWaitList.push_back(eventKernel); - - // Runs the post-processing kernel - auto upper = (triangle == Triangle::kUpper); - auto lower = (triangle == Triangle::kLower); - status = PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, - n_ceiled, n_ceiled, n_ceiled, 0, c_temp, - n, n, c_ld, c_offset, c_buffer, - ConstantOne(), program, - false, c_rotated, false, upper, lower, false); - if (ErrorIn(status)) { return status; } - - - // Successfully finished the computation - return StatusCode::kSuccess; - } catch (...) { return StatusCode::kInvalidKernel; } - } catch (...) { return StatusCode::kTempBufferAllocFailure; } + // Loads the program from the database + const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); + + // Determines whether or not temporary matrices are needed + auto a_no_temp = a_one == n_ceiled && a_two == k_ceiled && a_ld == n_ceiled && a_offset == 0 && + a_rotated == false; + + // Creates the temporary matrices + auto a_temp = (a_no_temp) ? a_buffer : Buffer(context_, k_ceiled*n_ceiled); + auto c_temp = Buffer(context_, n_ceiled*n_ceiled); + + // Events of all kernels (including pre/post processing kernels) + auto eventWaitList = std::vector(); + auto emptyEventList = std::vector(); + + // Runs the pre-processing kernel for matrix A. This transposes the matrix, but also pads zeros + // to fill it up until it reaches a certain multiple of size (kernel parameter dependent). In + // case nothing has to be done, these kernels can be skipped. + if (!a_no_temp) { + auto eventProcessA = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessA.pointer(), emptyEventList, + a_one, a_two, a_ld, a_offset, a_buffer, + n_ceiled, k_ceiled, n_ceiled, 0, a_temp, + ConstantOne(), program, + true, a_rotated, false); + eventWaitList.push_back(eventProcessA); + } + + // Furthermore, also creates a (possibly padded) copy of matrix C, since it is not allowed to + // modify the other triangle. + auto eventProcessC = Event(); + PadCopyTransposeMatrix(queue_, device_, db_, eventProcessC.pointer(), emptyEventList, + n, n, c_ld, c_offset, c_buffer, + n_ceiled, n_ceiled, n_ceiled, 0, c_temp, + ConstantOne(), program, + true, c_rotated, false); + eventWaitList.push_back(eventProcessC); + + // Retrieves the XgemmUpper or XgemmLower kernel from the compiled binary + auto kernel = Kernel(program, kernel_name); + + // Sets the kernel arguments + kernel.SetArgument(0, static_cast(n_ceiled)); + kernel.SetArgument(1, static_cast(k_ceiled)); + kernel.SetArgument(2, GetRealArg(alpha)); + kernel.SetArgument(3, GetRealArg(beta)); + kernel.SetArgument(4, a_temp()); + kernel.SetArgument(5, a_temp()); + kernel.SetArgument(6, c_temp()); + + // Computes the global and local thread sizes + auto global = std::vector{ + (n_ceiled * db_["MDIMC"]) / db_["MWG"], + (n_ceiled * db_["NDIMC"]) / db_["NWG"] + }; + auto local = std::vector{db_["MDIMC"], db_["NDIMC"]}; + + // Launches the kernel + auto eventKernel = Event(); + RunKernel(kernel, queue_, device_, global, local, eventKernel.pointer(), eventWaitList); + eventWaitList.push_back(eventKernel); + + // Runs the post-processing kernel + auto upper = (triangle == Triangle::kUpper); + auto lower = (triangle == Triangle::kLower); + PadCopyTransposeMatrix(queue_, device_, db_, event_, eventWaitList, + n_ceiled, n_ceiled, n_ceiled, 0, c_temp, + n, n, c_ld, c_offset, c_buffer, + ConstantOne(), program, + false, c_rotated, false, upper, lower, false); } // ================================================================================================= diff --git a/src/routines/level3/xsyrk.hpp b/src/routines/level3/xsyrk.hpp index 7c075c26..de42b824 100644 --- a/src/routines/level3/xsyrk.hpp +++ b/src/routines/level3/xsyrk.hpp @@ -32,12 +32,12 @@ class Xsyrk: public Routine { Xsyrk(Queue &queue, EventPointer event, const std::string &name = "SYRK"); // Templated-precision implementation of the routine - StatusCode DoSyrk(const Layout layout, const Triangle triangle, const Transpose a_transpose, - const size_t n, const size_t k, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const T beta, - const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); + void DoSyrk(const Layout layout, const Triangle triangle, const Transpose a_transpose, + const size_t n, const size_t k, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const T beta, + const Buffer &c_buffer, const size_t c_offset, const size_t c_ld); }; // ================================================================================================= diff --git a/src/routines/level3/xtrmm.cpp b/src/routines/level3/xtrmm.cpp index 74a82822..6bf77cfa 100644 --- a/src/routines/level3/xtrmm.cpp +++ b/src/routines/level3/xtrmm.cpp @@ -29,7 +29,7 @@ Xtrmm::Xtrmm(Queue &queue, EventPointer event, const std::string &name): // The main routine template -StatusCode Xtrmm::DoTrmm(const Layout layout, const Side side, const Triangle triangle, +void Xtrmm::DoTrmm(const Layout layout, const Side side, const Triangle triangle, const Transpose a_transpose, const Diagonal diagonal, const size_t m, const size_t n, const T alpha, @@ -37,15 +37,14 @@ StatusCode Xtrmm::DoTrmm(const Layout layout, const Side side, const Triangle const Buffer &b_buffer, const size_t b_offset, const size_t b_ld) { // Makes sure all dimensions are larger than zero - if ((m == 0) || (n == 0)) { return StatusCode::kInvalidDimension; } + if ((m == 0) || (n == 0)) { throw BLASError(StatusCode::kInvalidDimension); } // Computes the k dimension. This is based on whether or not matrix is A (on the left) // or B (on the right) in the Xgemm routine. auto k = (side == Side::kLeft) ? m : n; // Checks for validity of the triangular A matrix - auto status = TestMatrixA(k, k, a_buffer, a_offset, a_ld); - if (ErrorIn(status)) { return status; } + TestMatrixA(k, k, a_buffer, a_offset, a_ld); // Determines which kernel to run based on the layout (the Xgemm kernel assumes column-major as // default) and on whether we are dealing with an upper or lower triangle of the triangular matrix @@ -57,74 +56,69 @@ StatusCode Xtrmm::DoTrmm(const Layout layout, const Side side, const Triangle auto unit_diagonal = (diagonal == Diagonal::kUnit) ? true : false; // Temporary buffer for a copy of the triangular matrix - try { - auto temp_triangular = Buffer(context_, k*k); - - // Creates a general matrix from the triangular matrix to be able to run the regular Xgemm - // routine afterwards + auto temp_triangular = Buffer(context_, k*k); + + // Creates a general matrix from the triangular matrix to be able to run the regular Xgemm + // routine afterwards + const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); + auto kernel = Kernel(program, kernel_name); + + // Sets the arguments for the triangular-to-squared kernel + kernel.SetArgument(0, static_cast(k)); + kernel.SetArgument(1, static_cast(a_ld)); + kernel.SetArgument(2, static_cast(a_offset)); + kernel.SetArgument(3, a_buffer()); + kernel.SetArgument(4, static_cast(k)); + kernel.SetArgument(5, static_cast(k)); + kernel.SetArgument(6, static_cast(0)); + kernel.SetArgument(7, temp_triangular()); + kernel.SetArgument(8, static_cast(unit_diagonal)); + + // Uses the common padding kernel's thread configuration. This is allowed, since the + // triangular-to-squared kernel uses the same parameters. + auto global = std::vector{Ceil(CeilDiv(k, db_["PAD_WPTX"]), db_["PAD_DIMX"]), + Ceil(CeilDiv(k, db_["PAD_WPTY"]), db_["PAD_DIMY"])}; + auto local = std::vector{db_["PAD_DIMX"], db_["PAD_DIMY"]}; + auto kernelEvent = Event(); + RunKernel(kernel, queue_, device_, global, local, kernelEvent.pointer()); + + // Synchronize now: 'DoGemm' does not accept a list of events to wait for + kernelEvent.WaitForCompletion(); + + // Runs the regular Xgemm code with either "B := alpha*A*B" or ... + if (side == Side::kLeft) { + DoGemm(layout, a_transpose, Transpose::kNo, + m, n, k, + alpha, + temp_triangular, 0, k, + b_buffer, b_offset, b_ld, + static_cast(0.0), + b_buffer, b_offset, b_ld); + } + + // ... with "B := alpha*B*A". Note that A and B are now reversed. + else { try { - const auto program = GetProgramFromCache(context_, PrecisionValue(), routine_name_); - auto kernel = Kernel(program, kernel_name); - - // Sets the arguments for the triangular-to-squared kernel - kernel.SetArgument(0, static_cast(k)); - kernel.SetArgument(1, static_cast(a_ld)); - kernel.SetArgument(2, static_cast(a_offset)); - kernel.SetArgument(3, a_buffer()); - kernel.SetArgument(4, static_cast(k)); - kernel.SetArgument(5, static_cast(k)); - kernel.SetArgument(6, static_cast(0)); - kernel.SetArgument(7, temp_triangular()); - kernel.SetArgument(8, static_cast(unit_diagonal)); - - // Uses the common padding kernel's thread configuration. This is allowed, since the - // triangular-to-squared kernel uses the same parameters. - auto global = std::vector{Ceil(CeilDiv(k, db_["PAD_WPTX"]), db_["PAD_DIMX"]), - Ceil(CeilDiv(k, db_["PAD_WPTY"]), db_["PAD_DIMY"])}; - auto local = std::vector{db_["PAD_DIMX"], db_["PAD_DIMY"]}; - auto kernelEvent = Event(); - status = RunKernel(kernel, queue_, device_, global, local, kernelEvent.pointer()); - if (ErrorIn(status)) { return status; } - - // Synchronize now: 'DoGemm' does not accept a list of events to wait for - kernelEvent.WaitForCompletion(); - - // Runs the regular Xgemm code with either "B := alpha*A*B" or ... - if (side == Side::kLeft) { - status = DoGemm(layout, a_transpose, Transpose::kNo, - m, n, k, - alpha, - temp_triangular, 0, k, - b_buffer, b_offset, b_ld, - static_cast(0.0), - b_buffer, b_offset, b_ld); - } - - // ... with "B := alpha*B*A". Note that A and B are now reversed. - else { - status = DoGemm(layout, Transpose::kNo, a_transpose, - m, n, k, - alpha, - b_buffer, b_offset, b_ld, - temp_triangular, 0, k, - static_cast(0.0), - b_buffer, b_offset, b_ld); - - // A and B are now reversed, so also reverse the error codes returned from the Xgemm routine - switch(status) { - case StatusCode::kInvalidMatrixA: status = StatusCode::kInvalidMatrixB; break; - case StatusCode::kInvalidMatrixB: status = StatusCode::kInvalidMatrixA; break; - case StatusCode::kInvalidLeadDimA: status = StatusCode::kInvalidLeadDimB; break; - case StatusCode::kInvalidLeadDimB: status = StatusCode::kInvalidLeadDimA; break; - case StatusCode::kInsufficientMemoryA: status = StatusCode::kInsufficientMemoryB; break; - case StatusCode::kInsufficientMemoryB: status = StatusCode::kInsufficientMemoryA; break; - } + DoGemm(layout, Transpose::kNo, a_transpose, + m, n, k, + alpha, + b_buffer, b_offset, b_ld, + temp_triangular, 0, k, + static_cast(0.0), + b_buffer, b_offset, b_ld); + } catch (BLASError &e) { + // A and B are now reversed, so also reverse the error codes returned from the Xgemm routine + switch(e.status()) { + case StatusCode::kInvalidMatrixA: throw BLASError(StatusCode::kInvalidMatrixB, e.details()); + case StatusCode::kInvalidMatrixB: throw BLASError(StatusCode::kInvalidMatrixA, e.details()); + case StatusCode::kInvalidLeadDimA: throw BLASError(StatusCode::kInvalidLeadDimB, e.details()); + case StatusCode::kInvalidLeadDimB: throw BLASError(StatusCode::kInvalidLeadDimA, e.details()); + case StatusCode::kInsufficientMemoryA: throw BLASError(StatusCode::kInsufficientMemoryB, e.details()); + case StatusCode::kInsufficientMemoryB: throw BLASError(StatusCode::kInsufficientMemoryA, e.details()); + default: throw; } - - // Return the status of the Xgemm routine - return status; - } catch (...) { return StatusCode::kInvalidKernel; } - } catch (...) { return StatusCode::kTempBufferAllocFailure; } + } + } } // ================================================================================================= diff --git a/src/routines/level3/xtrmm.hpp b/src/routines/level3/xtrmm.hpp index 186a120e..967bf132 100644 --- a/src/routines/level3/xtrmm.hpp +++ b/src/routines/level3/xtrmm.hpp @@ -38,12 +38,12 @@ class Xtrmm: public Xgemm { Xtrmm(Queue &queue, EventPointer event, const std::string &name = "TRMM"); // Templated-precision implementation of the routine - StatusCode DoTrmm(const Layout layout, const Side side, const Triangle triangle, - const Transpose a_transpose, const Diagonal diagonal, - const size_t m, const size_t n, - const T alpha, - const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, - const Buffer &b_buffer, const size_t b_offset, const size_t b_ld); + void DoTrmm(const Layout layout, const Side side, const Triangle triangle, + const Transpose a_transpose, const Diagonal diagonal, + const size_t m, const size_t n, + const T alpha, + const Buffer &a_buffer, const size_t a_offset, const size_t a_ld, + const Buffer &b_buffer, const size_t b_offset, const size_t b_ld); }; // ================================================================================================= -- cgit v1.2.3