Added the HERK routine, tester, and client

1 files changed, 156 insertions, 0 deletions

diff --git a/src/routines/xherk.cc b/src/routines/xherk.cc
new file mode 100644
index 00000000..6bc9cd6c
--- /dev/null
+++ b/src/routines/xherk.cc
@@ -0,0 +1,156 @@
+
+// =================================================================================================
+// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This
+// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max-
+// width of 100 characters per line.
+//
+// Author(s):
+//   Cedric Nugteren <www.cedricnugteren.nl>
+//
+// This file implements the Xherk class (see the header for information about the class).
+//
+// =================================================================================================
+
+#include "internal/routines/xherk.h"
+
+#include <string>
+#include <vector>
+
+namespace clblast {
+// =================================================================================================
+
+// Specific implementations to get the memory-type based on a template argument
+template <> const Precision Xherk<float2,float>::precision_ = Precision::kComplexSingle;
+template <> const Precision Xherk<double2,double>::precision_ = Precision::kComplexDouble;
+
+// =================================================================================================
+
+// Constructor: forwards to base class constructor
+template <typename T, typename U>
+Xherk<T,U>::Xherk(CommandQueue &queue, Event &event):
+    Routine(queue, event, {"Copy", "Pad", "Transpose", "PadTranspose", "Xgemm"}, precision_) {
+}
+
+// =================================================================================================
+
+// The main routine
+template <typename T, typename U>
+StatusCode Xherk<T,U>::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) {
+
+  // Makes sure all dimensions are larger than zero
+  if ((n == 0) || (k == 0) ) { return StatusCode::kInvalidDimension; }
+
+  // Determines whether to apply the conjugate transpose to matrix B (argument: no transpose) or
+  // to matrix A (argument: conjugate transpose)
+  auto a_conjugate = (a_transpose != Transpose::kNo);
+  auto b_conjugate = (a_transpose == Transpose::kNo);
+
+  // 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.
+  auto a_rotated = (layout == Layout::kColMajor && a_conjugate) ||
+                   (layout == Layout::kRowMajor && !a_conjugate);
+  auto c_rotated = (layout == Layout::kRowMajor);
+
+  // Computes the first and second dimensions of the A matrix taking the layout into account
+  auto a_one = (a_rotated) ? k : n;
+  auto a_two = (a_rotated) ? n : k;
+
+  // Tests the two matrices (A, C) for validity, first from a perspective of the OpenCL buffers and
+  // their sizes, and then from a perspective of parameter values (e.g. n, k). Tests whether the
+  // OpenCL buffers are valid and non-zero and whether the OpenCL buffers have sufficient storage
+  // 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, sizeof(T));
+  if (ErrorIn(status)) { return status; }
+  status = TestMatrixC(n, n, c_buffer, c_offset, c_ld, sizeof(T));
+  if (ErrorIn(status)) { return status; }
+
+  // Calculates the ceiled versions of n and k
+  auto n_ceiled = Ceil(n, db_["NWG"]);
+  auto k_ceiled = Ceil(k, db_["KWG"]);
+
+  // Decides which kernel to run: the upper-triangular or lower-triangular version
+  auto kernel_name = (triangle == Triangle::kUpper) ? "XgemmUpper" : "XgemmLower";
+
+  // Allocates space on the device for padded and/or transposed input and output matrices.
+  try {
+    auto temp_a = Buffer(context_, CL_MEM_READ_WRITE, k_ceiled*n_ceiled*sizeof(T));
+    auto temp_b = Buffer(context_, CL_MEM_READ_WRITE, k_ceiled*n_ceiled*sizeof(T));
+    auto temp_c = Buffer(context_, CL_MEM_READ_WRITE, n_ceiled*n_ceiled*sizeof(T));
+
+    // Loads the program from the database
+    auto& program = GetProgramFromCache();
+
+    // Runs the pre-processing kernel. This transposes the matrix A, but also pads zeros to
+    // fill it up until it reaches a certain multiple of size (kernel parameter dependent). It
+    // creates two copies: 
+    status = PadCopyTransposeMatrix(a_one, a_two, a_ld, a_offset, a_buffer,
+                                    n_ceiled, k_ceiled, n_ceiled, 0, temp_a,
+                                    a_rotated, a_conjugate, true, false, false, false, program);
+    if (ErrorIn(status)) { return status; }
+    status = PadCopyTransposeMatrix(a_one, a_two, a_ld, a_offset, a_buffer,
+                                    n_ceiled, k_ceiled, n_ceiled, 0, temp_b,
+                                    a_rotated, b_conjugate, true, false, false, false, program);
+    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.
+    status = PadCopyTransposeMatrix(n, n, c_ld, c_offset, c_buffer,
+                                    n_ceiled, n_ceiled, n_ceiled, 0, temp_c,
+                                    c_rotated, false, true, false, false, false, program);
+    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
+      auto complex_alpha = T{alpha, static_cast<U>(0.0)};
+      auto complex_beta = T{beta, static_cast<U>(0.0)};
+      kernel.SetArgument(0, static_cast<int>(n_ceiled));
+      kernel.SetArgument(1, static_cast<int>(k_ceiled));
+      kernel.SetArgument(2, complex_alpha);
+      kernel.SetArgument(3, complex_beta);
+      kernel.SetArgument(4, temp_a());
+      kernel.SetArgument(5, temp_b());
+      kernel.SetArgument(6, temp_c());
+
+      // Computes the global and local thread sizes
+      auto global = std::vector<size_t>{
+        (n_ceiled * db_["MDIMC"]) / db_["MWG"],
+        (n_ceiled * db_["NDIMC"]) / db_["NWG"]
+      };
+      auto local = std::vector<size_t>{db_["MDIMC"], db_["NDIMC"]};
+
+      // Launches the kernel
+      status = RunKernel(kernel, global, local);
+      if (ErrorIn(status)) { return status; }
+
+      // Runs the post-processing kernel
+      auto upper = (triangle == Triangle::kUpper);
+      auto lower = (triangle == Triangle::kLower);
+      status = PadCopyTransposeMatrix(n_ceiled, n_ceiled, n_ceiled, 0, temp_c,
+                                      n, n, c_ld, c_offset, c_buffer,
+                                      c_rotated, false, false, upper, lower, true, program);
+      if (ErrorIn(status)) { return status; }
+
+      // Successfully finished the computation
+      return StatusCode::kSuccess;
+    } catch (...) { return StatusCode::kInvalidKernel; }
+  } catch (...) { return StatusCode::kTempBufferAllocFailure; }
+}
+
+// =================================================================================================
+
+// Compiles the templated class
+template class Xherk<float2,float>;
+template class Xherk<double2,double>;
+
+// =================================================================================================
+} // namespace clblast