| Manufacturer/Processor Type, Speed, Count, Threads, Processes |
| Includes the manufacturer/processor type, processor speed, number of processors, threads, and number of processes. Move mouse over this column for each row to display additional information, including; manufacturer, system name, interconnect, MPI, affiliation, and submission date. |
| Computer System |
| Name and version of Message Passing Interface (MPI) implementation.
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| Run Type |
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Run Type, indicates whether the benchmark was a base run or was optimized. |
| Processors |
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Processors, this is the number of processors used in the benchmark, entered in the form by the benchmark submitter. |
| G-HPL ( system performance ) |
| HPL, solves a randomly generated dense linear system of equations in double floating-point precision (IEEE 64-bit) arithmetic using MPI. The linear system matrix is stored in a two-dimensional block-cyclic fashion and multiple variants of code are provided for computational kernels and communication patterns. The solution method is LU factorization through Gaussian elimination with partial row pivoting followed by a backward substitution. Unit: Tera Flops per Second |
| EP-DGEMM ( per process ) |
| Embarrassingly Parallel DGEMM, benchmark measures the floating-point execution rate of double precision real matrix-matrix multiply performed by the DGEMM subroutine from the BLAS (Basic Linear Algebra Subprograms). It is run in embarrassingly parallel manner - all computational processes perform the benchmark at the same time, the arithmetic average rate is reported. Unit: Giga Flops per Second |
| EP-STREAM ( per process ) |
| The Embarrassingly Parallel STREAM benchmark is a simple synthetic benchmark program that measures sustainable memory bandwidth and the corresponding computation rate for simple vector kernels. It is run in embarrassingly parallel manner - all computational processes perform the benchmark at the same time, the average is computed. Unit: Giga Bytes per Second |
| EP-RandomAccess ( per process ) |
| Embarrassingly Parallel Random Access - (also called GUPs), measures the rate at which the computer can update pseudo-random locations of its memory. The embarrassingly parallel version runs the code locally on each processor. No explicit communication is performed (but shared-memory effects might occur). Unit: Giga Updates per Second |
| EP-FFTE ( per process ) |
| Embarrassingly Parallel FFTE, performs the same test as FFT but in embarrassingly parallel fashion - the code is run locally on each processor. No explicit communication is performed (but shared-memory effects might occur). Unit: Giga Flops per Second |
| Description above |
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| Description below |
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