Overview of the Intel® Distribution for LINPACK* Benchmark
The Intel® Distribution for LINPACK* Benchmark is based on modifications and additions to High-Performance LINPACK (HPL) (http://www.netlib.org/benchmark/hpl/) from Innovative Computing Laboratories (ICL) at the University of Tennessee, Knoxville. The Intel® Distribution for LINPACK Benchmark can be used for TOP500 runs (see http://www.top500.org) and for benchmarking your cluster. To use the benchmark, you must be familiar with HPL usage. The Intel® Distribution for LINPACK Benchmark provides some enhancements designed to make the HPL usage more convenient and to use Intel® Message-Passing Interface (MPI) settings to improve performance.
The Intel® Distribution for LINPACK Benchmark measures the amount of time it takes to factor and solve a random dense system of linear equations (Ax=b) in real*8 precision, converts that time into a performance rate, and tests the results for accuracy. The benchmark uses random number generation and full row pivoting to ensure the accuracy of the results.
Intel provides optimized versions of the LINPACK benchmarks to help you obtain high LINPACK benchmark results on your systems based on genuine Intel processors more easily than with the standard HPL benchmark. The prebuilt binaries require Intel® MPI library be installed on the cluster. The run-time version of Intel MPI library is free and can be downloaded from https://www.intel.com/content/www/us/en/developer/tools/overview.html.
The Intel package includes software developed at the University of Tennessee, Knoxville, ICL, and neither the University nor ICL endorse or promote this product. Although HPL is redistributable under certain conditions, this particular package is subject to the Intel® oneAPI Math Kernel Library (oneMKL) license.
HPL code is homogeneous by nature: it requires that each MPI process runs in an environment with similar CPU and memory constraints. The Intel® Distribution for LINPACK Benchmark supports heterogeneity, meaning that the data distribution can be balanced to the performance requirements of each node, provided that there is enough memory on that node to support additional work. For information on how to configure Intel® oneAPI Math Kernel Library (oneMKL) to use the internode heterogeneity, see Heterogeneous Support in the Intel® Distribution for LINPACK Benchmark.
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.
Notice revision #20201201