Bring your business’s best ideas to life by transforming big data and real-time analytics into new business opportunities while ensuring the reliability and uptime of the most business-critical services with new Intel® Xeon® Scalable processors.
Technical computing is the application of the mathematical and computational principles of scientific computing to solve practical problems of industrial interest. The distinction between technical computing and scientific computing is similar to the distinction between high-performance computing and high-performance technical computing. Technical computing may involve the use of large-scale high-performance systems.
All performance measurements are accurate as of July 11 2017.
This CPU-intensive benchmark suite, stressing a system's processor, memory subsystem, and compiler provides a comparative measure of compute-intensive performance across the widest practical range of hardware using workloads developed from real user applications. Rate results measure the throughput of multiple tasks. The metrics are based on a geometric mean of normalized ratios. CFP 2006 is for measuring and comparing compute-intensive floating point performance across 17 workloads or tasks.
This CPU-intensive benchmark suite, stressing a system's processor, memory subsystem, and compiler provides a comparative measure of compute-intensive performance across the widest practical range of hardware using workloads developed from real user applications. Speed results determine the time required to complete a single task. The metrics are based on a geometric mean of normalized ratios. CFP2006 is for measuring and comparing compute-intensive floating point performance across 17 workloads or tasks written in Fortran, C, and C++.
The Intel® Distribution for LINPACK* Benchmark is based on modifications and additions to High-Performance LINPACK (HPL) 2.1 from Innovative Computing Laboratories (ICL) at the University of Tennessee, Knoxville. This 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.
