Math Kernel Library Developer Guide
The Intel® Optimized High Performance Conjugate Gradient Benchmark (Intel® Optimized HPCG) provides an implementation of the HPCG benchmark (http://hpcg-benchmark.org) optimized for Intel® Xeon® processors and Intel® Xeon Phi™ processors with Intel® Advanced Vector Extensions (Intel® AVX), Intel® Advanced Vector Extensions 2 (Intel® AVX2), Intel® Advanced Vector Extensions 512 (Intel® AVX-512) support. The HPCG Benchmark is intended to complement the High Performance LINPACK benchmark used in the TOP500 (http://www.top500.org) system ranking by providing a metric that better aligns with a broader set of important cluster applications.
The HPCG benchmark implementation is based on a 3-dimensional (3D) regular 27-point discretization of an elliptic partial differential equation. The implementation calls a 3D domain to fill a 3D virtual process grid for all the available MPI ranks. HPCG uses the preconditioned conjugate gradient method (CG) to solve the intermediate systems of equations and incorporates a local and symmetric Gauss-Seidel preconditioning step that requires a triangular forward solve and a backward solve. A synthetic multi-grid V-cycle is used on each preconditioning step to make the benchmark better fit real-world applications. HPCG implements matrix multiplication locally, with an initial halo exchange between neighboring processes. The benchmark exhibits irregular accesses to memory and fine-grain recursive computations that dominate many scientific workloads (for details, see http://www.sandia.gov/~maherou/docs/HPCG-Benchmark.pdf).
The Intel® Optimized HPCG contains source code of the HPCG v3.0 reference implementation with necessary modifications to include:
Intel® architecture optimizations
Prebuilt benchmark executables that link to
Sparse triangular solve (TRSV)
Symmetric Gauss-Seidel smoother (SYMGS)
The Intel® oneAPI Math Kernel Library Inspector-executor Sparse BLAS kernels SpMV, TRSV, and SYMGS are implemented using an inspector-executor model. The inspection step chooses the best algorithm for the input matrix and converts the matrix to a special internal representation to achieve high performance at the execution step.
Optimization Notice |
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Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. Notice revision #20110804 |