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diff --git a/src/routines/level3/xherk.cpp b/src/routines/level3/xherk.cpp
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+
+// =================================================================================================
+// 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 "routines/level3/xherk.hpp"
+
+#include <string>
+#include <vector>
+
+namespace clblast {
+// =================================================================================================
+
+// Constructor: forwards to base class constructor
+template <typename T, typename U>
+Xherk<T,U>::Xherk(Queue &queue, EventPointer event, const std::string &name):
+    Routine(queue, event, name, {"Copy","Pad","Transpose","Padtranspose","Xgemm"}, PrecisionValue<T>()) {
+  source_string_ =
+    #include "../../kernels/level3/level3.opencl"
+    #include "../../kernels/level3/copy_fast.opencl"
+    #include "../../kernels/level3/copy_pad.opencl"
+    #include "../../kernels/level3/transpose_fast.opencl"
+    #include "../../kernels/level3/transpose_pad.opencl"
+    #include "../../kernels/level3/xgemm_part1.opencl"
+    #include "../../kernels/level3/xgemm_part2.opencl"
+  ;
+}
+
+// =================================================================================================
+
+// 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<T> &a_buffer, const size_t a_offset, const size_t a_ld,
+                              const U beta,
+                              const Buffer<T> &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);
+  if (ErrorIn(status)) { return status; }
+  status = TestMatrixC(n, n, c_buffer, c_offset, c_ld);
+  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";
+
+  // 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<T>(), 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<T>(context_, k_ceiled*n_ceiled);
+    auto b_temp = (b_no_temp) ? a_buffer : Buffer<T>(context_, k_ceiled*n_ceiled);
+    auto c_temp = Buffer<T>(context_, n_ceiled*n_ceiled);
+
+    // Upload the scalar arguments as constant buffers to the device (needed for half-precision)
+    auto complex_alpha = T{alpha, static_cast<U>(0.0)};
+    auto complex_beta = T{beta, static_cast<U>(0.0)};
+    auto alpha_buffer = Buffer<T>(context_, 1);
+    auto beta_buffer = Buffer<T>(context_, 1);
+    alpha_buffer.Write(queue_, 1, &complex_alpha);
+    beta_buffer.Write(queue_, 1, &complex_beta);
+
+    // Events of all kernels (including pre/post processing kernels)
+    auto eventWaitList = std::vector<Event>();
+    auto emptyEventList = std::vector<Event>();
+
+    // 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_, context_, db_, eventProcessA.pointer(), emptyEventList,
+                                      a_one, a_two, a_ld, a_offset, a_buffer,
+                                      n_ceiled, k_ceiled, n_ceiled, 0, a_temp,
+                                      ConstantOne<T>(), 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_, context_, db_, eventProcessB.pointer(), emptyEventList,
+                                      a_one, a_two, a_ld, a_offset, a_buffer,
+                                      n_ceiled, k_ceiled, n_ceiled, 0, b_temp,
+                                      ConstantOne<T>(), 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_, context_, db_, eventProcessC.pointer(), emptyEventList,
+                                    n, n, c_ld, c_offset, c_buffer,
+                                    n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
+                                    ConstantOne<T>(), 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<int>(n_ceiled));
+      kernel.SetArgument(1, static_cast<int>(k_ceiled));
+      kernel.SetArgument(2, alpha_buffer());
+      kernel.SetArgument(3, beta_buffer());
+      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<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
+      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_, context_, db_, event_, eventWaitList,
+                                      n_ceiled, n_ceiled, n_ceiled, 0, c_temp,
+                                      n, n, c_ld, c_offset, c_buffer,
+                                      ConstantOne<T>(), 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; }
+}
+
+// =================================================================================================
+
+// Compiles the templated class
+template class Xherk<float2,float>;
+template class Xherk<double2,double>;
+
+// =================================================================================================
+} // namespace clblast