add miniapp triangular multiplication

miniapp/CMakeLists.txt

@@ -39,6 +39,8 @@ DLAF_addMiniapp(miniapp_bt_reduction_to_band SOURCES miniapp_bt_reduction_to_ban
 
 DLAF_addMiniapp(miniapp_triangular_solver SOURCES miniapp_triangular_solver.cpp)
 
+DLAF_addMiniapp(miniapp_triangular_multiplication SOURCES miniapp_triangular_multiplication.cpp)
+
 DLAF_addMiniapp(miniapp_eigensolver SOURCES miniapp_eigensolver.cpp)
 
 DLAF_addMiniapp(miniapp_gen_eigensolver SOURCES miniapp_gen_eigensolver.cpp)

miniapp/miniapp_triangular_multiplication.cpp

@@ -0,0 +1,288 @@
+//
+// Distributed Linear Algebra with Future (DLAF)
+//
+// Copyright (c) 2018-2023, ETH Zurich
+// All rights reserved.
+//
+// Please, refer to the LICENSE file in the root directory.
+// SPDX-License-Identifier: BSD-3-Clause
+//
+
+#include <cstdlib>
+#include <iostream>
+#include <limits>
+#include <type_traits>
+
+#include <blas/util.hh>
+#include <mpi.h>
+
+#include <pika/init.hpp>
+#include <pika/program_options.hpp>
+#include <pika/runtime.hpp>
+
+#include <dlaf/common/format_short.h>
+#include <dlaf/common/index2d.h>
+#include <dlaf/common/range2d.h>
+#include <dlaf/common/timer.h>
+#include <dlaf/communication/communicator_grid.h>
+#include <dlaf/communication/init.h>
+#include <dlaf/init.h>
+#include <dlaf/matrix/copy.h>
+#include <dlaf/matrix/index.h>
+#include <dlaf/matrix/matrix_mirror.h>
+#include <dlaf/miniapp/dispatch.h>
+#include <dlaf/miniapp/options.h>
+#include <dlaf/multiplication/triangular.h>
+#include <dlaf/types.h>
+#include <dlaf/util_matrix.h>
+
+namespace {
+
+using dlaf::Backend;
+using dlaf::DefaultDevice_v;
+using dlaf::Device;
+using dlaf::GlobalElementIndex;
+using dlaf::GlobalElementSize;
+using dlaf::SizeType;
+using dlaf::TileElementSize;
+using dlaf::comm::Communicator;
+using dlaf::comm::CommunicatorGrid;
+using dlaf::common::Ordering;
+
+struct Options
+    : dlaf::miniapp::MiniappOptions<dlaf::miniapp::SupportReal::Yes, dlaf::miniapp::SupportComplex::No> {
+  SizeType m;
+  SizeType n;
+  SizeType mb;
+  SizeType nb;
+  blas::Side side;
+  blas::Uplo uplo;
+  blas::Op op;
+  blas::Diag diag;
+
+  Options(const pika::program_options::variables_map& vm)
+      : MiniappOptions(vm), m(vm["m"].as<SizeType>()), n(vm["n"].as<SizeType>()),
+        mb(vm["mb"].as<SizeType>()), nb(vm["nb"].as<SizeType>()),
+        side(dlaf::miniapp::parseSide(vm["side"].as<std::string>())),
+        uplo(dlaf::miniapp::parseUplo(vm["uplo"].as<std::string>())),
+        op(dlaf::miniapp::parseOp(vm["op"].as<std::string>())),
+        diag(dlaf::miniapp::parseDiag(vm["diag"].as<std::string>())) {
+    DLAF_ASSERT(m > 0 && n > 0, m, n);
+    DLAF_ASSERT(mb > 0 && nb > 0, mb, nb);
+
+    if (do_check != dlaf::miniapp::CheckIterFreq::None) {
+      std::cerr << "Warning! At the moment result checking it is not implemented." << std::endl;
+      do_check = dlaf::miniapp::CheckIterFreq::None;
+    }
+  }
+
+  Options(Options&&) = default;
+  Options(const Options&) = default;
+  Options& operator=(Options&&) = default;
+  Options& operator=(const Options&) = default;
+};
+
+template <typename T>
+using matrix_values_t = std::function<T(const GlobalElementIndex&)>;
+
+template <typename T>
+using linear_system_t =
+    std::tuple<matrix_values_t<T>, matrix_values_t<T>, matrix_values_t<T>>;  // A, B, X
+
+template <typename T>
+linear_system_t<T> sampleLeftTr(blas::Uplo uplo, blas::Op op, blas::Diag diag, T alpha, SizeType m);
+}
+
+struct triangularMultiplicationMiniapp {
+  template <dlaf::Backend backend, typename T>
+  static void run(const Options& opts) {
+    Communicator world(MPI_COMM_WORLD);
+    CommunicatorGrid comm_grid(world, opts.grid_rows, opts.grid_cols, Ordering::ColumnMajor);
+
+    // Allocate memory for the matrices
+    dlaf::matrix::Matrix<T, Device::CPU> ah(GlobalElementSize{opts.m, opts.m},
+                                            TileElementSize{opts.mb, opts.mb}, comm_grid);
+    dlaf::matrix::Matrix<T, Device::CPU> bh(GlobalElementSize{opts.m, opts.n},
+                                            TileElementSize{opts.mb, opts.nb}, comm_grid);
+
+    dlaf::matrix::MatrixMirror<T, DefaultDevice_v<backend>, Device::CPU> a(ah);
+    dlaf::matrix::MatrixMirror<T, DefaultDevice_v<backend>, Device::CPU> b(bh);
+
+    auto sync_barrier = [&]() {
+      a.get().waitLocalTiles();
+      b.get().waitLocalTiles();
+      DLAF_MPI_CHECK_ERROR(MPI_Barrier(world));
+    };
+
+    const auto side = opts.side;
+    DLAF_ASSERT(side == blas::Side::Left, side);
+
+    const auto uplo = opts.uplo;
+    const auto op = opts.op;
+    const auto diag = opts.diag;
+    const T alpha = 2.0;
+
+    double m = ah.size().rows();
+    double n = bh.size().cols();
+    auto add_mul = n * m * m / 2;
+    const double total_ops = dlaf::total_ops<T>(add_mul, add_mul);
+
+    auto [in_op_a, out_b, in_b] = ::sampleLeftTr(uplo, op, diag, alpha, ah.size().rows());
+
+    for (int64_t run_index = -opts.nwarmups; run_index < opts.nruns; ++run_index) {
+      if (0 == world.rank() && run_index >= 0)
+        std::cout << "[" << run_index << "]" << std::endl;
+
+      // setup matrix A and b
+      using dlaf::matrix::util::set;
+      set(ah, in_op_a, op);
+      set(bh, in_b);
+      a.copySourceToTarget();
+      b.copySourceToTarget();
+
+      sync_barrier();
+
+      dlaf::common::Timer<> timeit;
+      if (opts.local)
+        dlaf::triangular_multiplication<backend, dlaf::DefaultDevice_v<backend>, T>(side, uplo, op, diag,
+                                                                                    alpha, a.get(),
+                                                                                    b.get());
+      else
+        dlaf::triangular_multiplication<backend, dlaf::DefaultDevice_v<backend>, T>(
+            comm_grid, side, uplo, op, diag, alpha, a.get(), b.get());
+
+      sync_barrier();
+
+      // benchmark results
+      if (0 == world.rank() && run_index >= 0) {
+        auto elapsed_time = timeit.elapsed();
+        double gigaflops = total_ops / elapsed_time / 1e9;
+
+        std::cout << "[" << run_index << "]"
+                  << " " << elapsed_time << "s"
+                  << " " << gigaflops << "GFlop/s"
+                  << " " << dlaf::internal::FormatShort{opts.type}
+                  << dlaf::internal::FormatShort{opts.side} << dlaf::internal::FormatShort{opts.uplo}
+                  << dlaf::internal::FormatShort{opts.op} << dlaf::internal::FormatShort{opts.diag}
+                  << " " << bh.size() << " " << bh.blockSize() << " " << comm_grid.size() << " "
+                  << pika::get_os_thread_count() << " " << backend << std::endl;
+      }
+
+      b.copyTargetToSource();
+
+      // (optional) run test
+      if ((opts.do_check == dlaf::miniapp::CheckIterFreq::Last && run_index == (opts.nruns - 1)) ||
+          opts.do_check == dlaf::miniapp::CheckIterFreq::All) {
+        DLAF_UNIMPLEMENTED("Check");
+      }
+    }
+  }
+};
+
+int pika_main(pika::program_options::variables_map& vm) {
+  pika::scoped_finalize pika_finalizer;
+  dlaf::ScopedInitializer init(vm);
+
+  const Options opts(vm);
+  dlaf::miniapp::dispatchMiniapp<triangularMultiplicationMiniapp>(opts);
+
+  return EXIT_SUCCESS;
+}
+
+int main(int argc, char** argv) {
+  dlaf::comm::mpi_init mpi_initter(argc, argv);
+
+  // options
+  using namespace pika::program_options;
+  options_description desc_commandline(
+      "Benchmark computation of A . B, "
+      "where A is a non-unit lower triangular matrix, and B is an m by n matrix\n\n"
+      "options\n"
+      "Usage: miniapp_triangular_multiplication [options]");
+  desc_commandline.add(dlaf::miniapp::getMiniappOptionsDescription());
+  desc_commandline.add(dlaf::getOptionsDescription());
+
+  // clang-format off
+  desc_commandline.add_options()
+    ("m",             value<SizeType>()     ->default_value(4096),       "Matrix b rows")
+    ("n",             value<SizeType>()     ->default_value(512),        "Matrix b columns")
+    ("mb",            value<SizeType>()     ->default_value(256),        "Matrix b block rows")
+    ("nb",            value<SizeType>()     ->default_value(512),        "Matrix b block columns")
+  ;
+  // clang-format on
+  dlaf::miniapp::addSideOption(desc_commandline);
+  dlaf::miniapp::addUploOption(desc_commandline);
+  dlaf::miniapp::addOpOption(desc_commandline);
+  dlaf::miniapp::addDiagOption(desc_commandline);
+
+  pika::init_params p;
+  p.desc_cmdline = desc_commandline;
+  p.rp_callback = dlaf::initResourcePartitionerHandler;
+  return pika::init(pika_main, argc, argv, p);
+}
+
+namespace {
+/// Returns a tuple of element generators of three matrices A(m x m), B (m x n), X (m x n), for which it
+/// holds op(A) X = alpha B (alpha can be any value).
+///
+/// The elements of op(A) (@p el_op_a) are chosen such that:
+///   op(A)_ik = (i+1) / (k+.5) * exp(I*(2*i-k)) for the referenced elements
+///   op(A)_ik = -9.9 otherwise,
+/// where I = 0 for real types or I is the complex unit for complex types.
+///
+/// The elements of X (@p el_x) are computed as
+///   X_kj = (k+.5) / (j+2) * exp(I*(k+j)).
+/// These data are typically used to check whether the result of the equation
+/// performed with any algorithm is consistent with the computed values.
+///
+/// Finally, the elements of B (@p el_b) should be:
+/// B_ij = (Sum_k op(A)_ik * X_kj) / alpha
+///      = (op(A)_ii * X_ij + (kk-1) * gamma) / alpha,
+/// where gamma = (i+1) / (j+2) * exp(I*(2*i+j)),
+///       kk = i+1 if op(a) is an lower triangular matrix, or
+///       kk = m-i if op(a) is an lower triangular matrix.
+/// Therefore
+/// B_ij = (X_ij + (kk-1) * gamma) / alpha, if diag == Unit
+/// B_ij = kk * gamma / alpha, otherwise.
+template <typename T>
+linear_system_t<T> sampleLeftTr(blas::Uplo uplo, blas::Op op, blas::Diag diag, T alpha, SizeType m) {
+  static_assert(std::is_arithmetic_v<T> && !std::is_integral_v<T>,
+                "it is valid just with floating point values");
+
+  bool op_a_lower = (uplo == blas::Uplo::Lower && op == blas::Op::NoTrans) ||
+                    (uplo == blas::Uplo::Upper && op != blas::Op::NoTrans);
+
+  auto el_op_a = [op_a_lower, diag](const GlobalElementIndex& index) -> T {
+    if ((op_a_lower && index.row() < index.col()) || (!op_a_lower && index.row() > index.col()) ||
+        (diag == blas::Diag::Unit && index.row() == index.col()))
+      return static_cast<T>(-9.9);
+
+    const T i = index.row();
+    const T k = index.col();
+
+    return (i + static_cast<T>(1)) / (k + static_cast<T>(.5));
+  };
+
+  auto el_x = [](const GlobalElementIndex& index) -> T {
+    const T k = index.row();
+    const T j = index.col();
+
+    return (k + static_cast<T>(.5)) / (j + static_cast<T>(2));
+  };
+
+  auto el_b = [m, alpha, diag, op_a_lower, el_x](const GlobalElementIndex& index) -> T {
+    const dlaf::BaseType<T> kk = op_a_lower ? index.row() + 1 : m - index.row();
+
+    const T i = index.row();
+    const T j = index.col();
+    const T gamma = (i + 1) / (j + 2);
+    if (diag == blas::Diag::Unit)
+      return ((kk - 1) * gamma + el_x(index)) / alpha;
+    else
+      return kk * gamma / alpha;
+  };
+
+  return {el_op_a, el_b, el_x};
+}
+
+}

miniapp/miniapp_triangular_solver.cpp

@@ -115,6 +115,7 @@ struct triangularSolverMiniapp {
     };
 
     const auto side = opts.side;
+    DLAF_ASSERT(side == blas::Side::Left, side);
     const auto uplo = opts.uplo;
     const auto op = opts.op;
     const auto diag = opts.diag;

scripts/miniapps.py

@@ -278,6 +278,41 @@ def trsm(
     return cmd, env.strip()
 
 
+def trmm(
+    system,
+    lib,
+    build_dir,
+    nodes,
+    rpn,
+    m_sz,
+    n_sz,
+    mb_sz,
+    nruns,
+    suffix="na",
+    extra_flags="",
+    env="",
+    dtype="d",
+):
+    if n_sz == None:
+        n_sz = m_sz
+
+    _check_ranks_per_node(system, lib, rpn)
+    [total_ranks, cores_per_rank, threads_per_rank] = _computeResourcesNeededList(system, nodes, rpn)
+    gr, gc = _sq_factor(total_ranks)
+
+    if lib.startswith("dlaf"):
+        _check_type(dtype)
+        env += " OMP_NUM_THREADS=1"
+        app = f"{build_dir}/miniapp/miniapp_triangular_multiplication"
+        opts = f"--type {dtype} --m {m_sz} --n {n_sz} --mb {mb_sz} --nb {mb_sz} --grid-rows {gr} --grid-cols {gc} --nruns {nruns} {extra_flags}"
+    else:
+        raise ValueError(_err_msg(lib))
+
+    _checkAppExec(app)
+    cmd = f"{app} {opts}".strip() + f" >> trmm_{lib}_{suffix}.out 2>&1"
+    return cmd, env.strip()
+
+
 # lib: allowed libraries are dlaf|slate
 # rpn: ranks per node
 #

scripts/plot_trmm_strong.py

@@ -0,0 +1,20 @@
+#!/usr/bin/env python3
+# coding: utf-8
+
+#
+# Distributed Linear Algebra with Future (DLAF)
+#
+# Copyright (c) 2018-2023, ETH Zurich
+# All rights reserved.
+#
+# Please, refer to the LICENSE file in the root directory.
+# SPDX-License-Identifier: BSD-3-Clause
+#
+
+import postprocess as pp
+
+df = pp.parse_jobs_cmdargs(description="Plot trmm strong scaling benchmarks.")
+
+df_grp = pp.calc_trmm_metrics(df)
+pp.gen_trmm_plots_strong(df_grp)
+pp.gen_trmm_plots_strong(df_grp, combine_mb=True)

scripts/plot_trmm_weak.py

@@ -0,0 +1,20 @@
+#!/usr/bin/env python3
+# coding: utf-8
+
+#
+# Distributed Linear Algebra with Future (DLAF)
+#
+# Copyright (c) 2018-2023, ETH Zurich
+# All rights reserved.
+#
+# Please, refer to the LICENSE file in the root directory.
+# SPDX-License-Identifier: BSD-3-Clause
+#
+
+import postprocess as pp
+
+df = pp.parse_jobs_cmdargs(description="Plot trmm weak scaling benchmarks.")
+
+df_grp = pp.calc_trmm_metrics(df)
+pp.gen_trmm_plots_weak(df_grp, 1024, logx=True)
+pp.gen_trmm_plots_weak(df_grp, 1024, logx=True, combine_mb=True)