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Timing results for BLAS (Basic Linear Algebra Subprograms) libraries in R
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README.md

BLAS libraries benchmarks

Andrzej Wójtowicz

Document generation date: 2016-07-14 17:20:41

This document presents timing results for BLAS (Basic Linear Algebra Subprograms) libraries in R on diverse CPUs and GPUs.

Changelog

  • 2016-07-14: results: added Intel Core i5-6500; changed results view of gcbd benchmark to relative performance gain; changed reference CPU (Intel Pentium Dual-Core E5300) and GPU (NVIDIA GeForce GT 630M); code: fixed target architecture detection for Intel Core i5-6500-like CPUs in multi-threaded Atlas library; added info how to force target architecture in GotoBLAS2 and BLIS libraries.

Table of Contents

  1. Configuration
  2. Results per host
  3. Results per library

Configuration

OS: Debian Jessie, kernel 4.4

R software: Microsoft R Open (3.2.4)

Libraries:

CPU (single-threaded) CPU (multi-threaded) GPU
Netlib (debian package, blas 1.2.20110419, lapack 3.5.0) OpenBLAS (debian package, 0.2.12) NVIDIA cuBLAS (NVBLAS 6.5 + Intel MKL)
ATLAS (debian package, 3.10.2) ATLAS (dev branch, 3.11.38)
GotoBLAS2 (Survive fork, 3.141)
Intel MKL (part of RevoMath package, 3.2.4)
BLIS (dev branch, 0.2.0+/17.05.2016)

Hosts:

No. CPU GPU
1. Intel Core i7-4790K (OC 4.5 GHz) MSI GeForce GTX 980 Ti Lightning
2. Intel Core i5-4590 NVIDIA GeForce GT 430
3. Intel Core i5-4590 NVIDIA GeForce GTX 750 Ti
4. Intel Core i5-6500 -
5. Intel Core i5-3570 -
6. Intel Core i3-2120 -
7. Intel Core i3-3120M -
8. Intel Core i5-3317U NVIDIA GeForce GT 630M
9. Intel Pentium Dual-Core E5300 -

Benchmarks: R-benchmark-25, Revolution, Gcbd.

Results per host

Intel Core i7-4790K + MSI GeForce GTX 980 Ti Lightning

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Intel Core i5-4590 + NVIDIA GeForce GT 430

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Intel Core i5-4590 + NVIDIA GeForce GTX 750 Ti

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Intel Core i5-6500

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Intel Core i5-3570

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Intel Core i3-2120

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Intel Core i3-3120M

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Intel Core i5-3317U + NVIDIA GeForce GT 630M

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Intel Pentium Dual-Core E5300

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

BLIS hangs in this test

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Netlib - from 50 to 5 runs - higher is better

Results per library

Netlib

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

ATLAS (st)

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

OpenBLAS

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

ATLAS (mt)

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

GotoBLAS2

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

MKL

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

BLIS

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Intel Pentium Dual-Core E5300 hangs in this test

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: Intel Pentium Dual-Core E5300 - from 50 to 5 runs - higher is better

cuBLAS

R-benchmark-25

2800x2800 cross-product matrix

Time in seconds - 10 runs - lower is better

Linear regr. over a 2000x2000 matrix

Time in seconds - 10 runs - lower is better

Eigenvalues of a 600x600 random matrix

Time in seconds - 10 runs - lower is better

Determinant of a 2500x2500 random matrix

Time in seconds - 10 runs - lower is better

Cholesky decomposition of a 3000x3000 matrix

Time in seconds - 10 runs - lower is better

Inverse of a 1600x1600 random matrix

Time in seconds - 10 runs - lower is better

Escoufier's method on a 45x45 matrix

Time in seconds - 10 runs - lower is better

Revolution benchmark

Matrix Multiply

Time in seconds - 10 runs - lower is better

Cholesky Factorization

Time in seconds - 10 runs - lower is better

Singular Value Deomposition

Time in seconds - 10 runs - lower is better

Principal Components Analysis

Time in seconds - 10 runs - lower is better

Linear Discriminant Analysis

Time in seconds - 10 runs - lower is better

Gcbd benchmark

Matrix Multiply

Performance gain regarding matrix size - reference: NVIDIA GeForce GT 630M - from 50 to 5 runs - higher is better

QR Decomposition

Performance gain regarding matrix size - reference: NVIDIA GeForce GT 630M - from 50 to 5 runs - higher is better

Singular Value Deomposition

Performance gain regarding matrix size - reference: NVIDIA GeForce GT 630M - from 50 to 5 runs - higher is better

Triangular Decomposition

Performance gain regarding matrix size - reference: NVIDIA GeForce GT 630M - from 50 to 5 runs - higher is better