#Rmax linpack benchmark 64 Bit#
#Rmax linpack benchmark full#
#Rmax linpack benchmark software#

The relative machine precision usually the smallest positive number such that fl( 1.0 - eps ) < 1.0, where fl denotes the computed value and eps is the relative machine precision.Дoes what it says: a very specialized test of math speed If this quantity is much larger than 1, the solution is probably incorrect. The Norm Res should be about O(1) in size. The test is based on || Ax - b || / ( || A || || x || eps) where eps is described below. The time in seconds to solve the problem, Ax=b.ДЄ check is made to show that the computed solution is correct. For this problem there are 2/3 n^3 + n^2 floating point operations.

#Rmax linpack benchmark 64 Bit#

A floating point operation here is a floating point addition or a floating point multiplication with 64 bit operands. Millions of floating point operations per second. The result is reported in millions of floating point operations per second (MFLOP/s, sometimes simply called FLOPS). The solution is obtained by Gaussian elimination with partial pivoting, with 2/3 They measure how fast a computer solves a dense N by N system of linear equations Ax = b, which is a common task in engineering.

: 1.The LINPACK Benchmarks are a measure of a system's floating point computing power. The results for this is below (11.73 GFlops) VVV-VVV-VVV-VVV-VVV-VVV-VVV-VVV-VVV-VVV-VVV-VVV-VVV-VVV-VVV.

This could also be one of those weird situations where native 64-bit runs slower than 32-bit compatibility mode.Д¬ode: Select all =

#Rmax linpack benchmark software#

It would be nice to know whether the differences in our timing results are related to the 8GB versus 2GB hardware, the matrix size, or some other software difference such as using the version 10.1 gcc compiler. The result is still greater than 10 GFLOPS. PASSEDДЇor some reason the version of MPICH I installed doesn't allow me to specify a rank file, so I can't check if that makes a difference. HPL_pdgesv() end time Fri Jun 5 04:54:15 2020ДЄlex, since I can't run the large matrix size with my 2GB Pi, would it be possible for you to try N=8000 and compare?Д¬ode: Select all $ export OPENBLAS_NUM_THREADS=1 I'll try to optimize the build and then post more details in case anyone wants to continue improving things.

#Rmax linpack benchmark full#

Likely the smaller matrix size gives slightly faster results than using the full memory size on the 8GB model. Note that MPICH was installed to use the slower ch3 network device rather than shared memory, but I think the run was using OpenBLAS threads rather than MPI anyway. PASSEDДЇinished 1 tests with the following results:ДЎ tests completed and passed residual checks,Д tests completed and failed residual checks,Д tests skipped because of illegal input values. Computational tests pass if scaled residuals are less than 16.0 The relative machine precision (eps) is taken to be 1.110223e-16 The following scaled residual check will be computed: The matrix A is randomly generated for each test. The following parameter values will be used:

Gflops : Rate of execution for solving the linear system. Time : Time in seconds to solve the linear system. N : The order of the coefficient matrix A. Modified by Julien Langou, University of Colorado DenverДЄn explanation of the input/output parameters follows: Modified by Piotr Luszczek, Innovative Computing Laboratory, UTK Clint Whaley, Innovative Computing Laboratory, UTK HPLinpack 2.3 - High-Performance Linpack benchmark - December 2, 2018