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Ultimate-SpMV

MPI+X SpM(M)V with SELL-C-sigma format

Can be run as a standalone benchmarking harness, or as a library. See API_doc.md for information about the interface.

Examples:
mpirun -n 4 ./uspmv <matrix_name>.mtx <kernel_format> <options>
./uspmv <matrix_name>.mtx scs -c 16 -s 512 -mode b
./uspmv <matrix_name>.mtx crs -mode s -block_vec_size 2 -verbose 1

  • kernel_format can be any one of: crs, scs (and by extention: ell and sell-p)

Options:

  • -block_vec_size (int: width of block X vector for SpMMV)
  • -c (int: chunk size (required for scs))
  • -s (int: sigma (required for scs))
  • -rev (int: number of back-to-back revisions to perform)
  • -rand_x (0/1: random x vector option)
  • -dp / sp / hp / ap[dp_sp] / ap[dp_hp] / ap[sp_hp] / ap[dp_sp_hp] (numerical precision of matrix data)
  • -seg_nnz/seg_rows/seg_metis (global matrix partitioning for MPI)
  • -validate (0/1: check result against MKL option)
  • -verbose (0/1: verbose validation of results)
  • -mode ('s'/'b': either in solve mode or bench mode)
  • -bench_time (float: minimum number of seconds for SpMV benchmark)
  • -ba_synch (0/1: synch processes each benchmark loop)
  • -comm_halos (0/1: communicate halo elements each benchmark loop)
  • -par_pack (0/1: pack elements contigously for MPI_Isend in parallel)
  • -ap_threshold_1 (float: threshold for two-way matrix partitioning for adaptive precision -ap)
  • -ap_threshold_2 (float: threshold for three-way matrix partitioning for adaptive precision -ap)
  • -dropout (0/1: enable dropout of elements below theh designated threshold)
  • -dropout_threshold (float: remove matrix elements below this range)
  • -equilibrate (0/1: normalize rows of matrix)

Notes:

  • This is a work in progress. Please report all issues, seg faults, and bugs on Github issues.
  • Please direct any suggestions/inquiries to my email dane.c.lacey at fau.de
  • The -c and -s options are only relevant when the scs kernel is selected
  • If interested in only single-vector SpMV, please select columnwise vector layout
  • Select compiler in Makefile (gcc, icc, icx, llvm, nvcc)
    • icc is legacy, and not advised
  • VECTOR_LENGTH for SIMD instructions is also defined at the top of the Makefile, useful for non-SELL_C_SIGMA kernels
  • If using AVX512 on icelake, I currently get around downfall perf bug with the icx compiler from OneAPI 2023.2.0
  • The par_pack option typically yields better performance for MPI+Openmp with poorly load balanced matrices
  • Thresholds for adaptive precision are expected in the order 0---TH2---TH1---\infty

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MPI+X SpM(M)V with SELL-C-sigma format

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