RAJA Portability Layer versions of PolyBench 4.2.1
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Latest commit a6ec07f Jul 28, 2016 @willkill07 (update) RAJA updated


PolyBench/C-RAJA 0.1.0

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PolyBench is a benchmark suite of 30 numerical computations with static control flow, extracted from operations in various application domains (linear algebra computations, image processing, physics simulation, dynamic programming, statistics, etc.).

Copyright (c) 2016 Lawrence Livermore National Laboratory

Copyright (c) 2016 University of Delaware


PolyBench/C 4.2.1

PolyBench was originally written by Louis-Noel Pouchet.

Copyright (c) 2011-2016 the Ohio State University.

PolyBench/C Contacts:

Changes from PolyBench/C

  • Using runtime multi-dimensional arrays with index computation lifted through templates
  • Base PolyBenchKernel abstract class for implementing kernels
  • Instrumentation can be extended or changed by modifying src/PolyBenchKernel.cpp
  • RAJA is included as a submodule of this repository
  • RAJA Portability Layer versions of each kernel are included as well as C++ versions of the original C kernels
  • All kernels are functionally equivalent. Some are parallelized; others just use simd_exec or seq_exec
  • There are four types of kernels currently in the source tree:
    • C++ Base -- basic C++ implementations of the PolyBench kernels
    • C++ OpenMP -- C++ implementations with OpenMP directives added
    • RAJA Base -- simd_exec and seq_exec RAJA execution policies
    • RAJA OpenMP -- omp_parallel_for_exec and omp_collapse_nowait_exec policies
  • Generic C++ drivers are provided in ./src/ but most edits should happen through ./include/<VERSION>/<KERNEL>.hpp
  • Dataset sizes are no longer stored with source code. They can be extracted from common/polybench.spec

Available benchmarks

Benchmark Description
2mm 2 Matrix Multiplications (alpha * A * B * C + beta * D)
3mm 3 Matrix Multiplications ((A * B) * (C * D))
adi Alternating Direction Implicit solver
atax Matrix Transpose and Vector Multiplication
bicg BiCG Sub Kernel of BiCGStab Linear Solver
cholesky Cholesky Decomposition
correlation Correlation Computation
covariance Covariance Computation
deriche Edge detection filter
doitgen Multi-resolution analysis kernel (MADNESS)
durbin Toeplitz system solver
fdtd-2d 2-D Finite Different Time Domain Kernel
gemm Matrix-multiply C=alpha.A.B+beta.C
gemver Vector Multiplication and Matrix Addition
gesummv Scalar, Vector and Matrix Multiplication
gramschmidt Gram-Schmidt decomposition
heat-3d Heat equation over 3D data domain
jacobi-1D 1-D Jacobi stencil computation
jacobi-2D 2-D Jacobi stencil computation
lu LU decomposition
ludcmp LU decomposition followed by Forward Substitution
mvt Matrix Vector Product and Transpose
nussinov Dynamic programming algorithm for sequence alignment
seidel 2-D Seidel stencil computation
symm Symmetric matrix-multiply
syr2k Symmetric rank-2k update
syrk Symmetric rank-k update
trisolv Triangular solver
trmm Triangular matrix-multiply