In order to verify the solution, the input matrix and the right-hand side are regenerated, and the normwise backward error is computed: Usually, it is chosen to maximize the problem size while still fitting the application in the RAM of the compute nodes. The size of the problem,, can be chosen arbitrarily. The solution is obtained by first computing the LU factorization with row partial pivoting and then solving a triangular system of equations. HPLinpack benchmark solves a system of linear algebraic equations of size , The systems are ranked according to their maximum LINPACK performance achieved. For instance, the TOP500 project provides a regularly updated list of the most powerful computer systems in the world ranked using HPL. The HPLinpack benchmark expressed as HPL is an industry-standard test of floating-point capabilities of parallel high-performance computing systems. At the same time, optimized versions of HPL for particular architectures exist (e.g., Intel-optimized HPL) and can be used without compilation.
#Intel linpack benchmark portable
HPL is portable because for linear algebra it interfaces with standard libraries, including the Basic Linear Algebra Subprograms (BLAS) and Linear Algebra Package (LAPACK), and uses the Message Passing Interface (MPI) for communication in a cluster.
#Intel linpack benchmark code
The code performs the benchmark workload and reports the timing and an estimate of the accuracy of the solution.
#Intel linpack benchmark software
HPL is a software package implementing the HPLinpack benchmark. To standardize the HPLinpack results, a code called HPL was developed. It expresses the performance of that system in floating-point operations per second (FLOP/s). The result of the HPLinpack benchmark is based on the time required to solve the system. The benchmark exercises the floating-point arithmetic units, the memory subsystem, and the communication fabric. The HPLinpack benchmark generates and solves on distributed-memory computers a large dense system of linear algebraic equations with random coefficients. The paper provides recipes that may be used to reproduce our results in environments similar to this cluster.Ĭolfax-HPL-Intel-Xeon-Phi-x200-and-Intel-Omni-Path-100.pdf (130 KB) Table of Contents Our benchmarks are taken on the Colfax Cluster, a state-of-the-art computing resource open to the public for benchmarking and code validation. We report the performance and a simplified tuning methodology of the HPLinpack benchmark on a cluster of Intel Xeon Phi processors 7250 with an Intel Omni-Path Fabric 100 Series interconnect.
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