)]}'
{
  "commit": "5d53d1ee3839d74cbc759785eceef9e225107dfb",
  "tree": "e57a4fe518e5f18c45640019c32f20ee66a8a6e4",
  "parents": [
    "9aa52c6ff74358d1b91542221e0545bb61bdedcc"
  ],
  "author": {
    "name": "Dmitriy Korchemkin",
    "email": "dmitriy.korchemkin@gmail.com",
    "time": "Wed Nov 02 16:06:48 2022 +0300"
  },
  "committer": {
    "name": "Dmitriy Korchemkin",
    "email": "dmitriy.korchemkin@gmail.com",
    "time": "Sat Nov 12 18:58:06 2022 +0300"
  },
  "message": "Parallel for with iteration costs and left product\n\nParallel for with user-supplied [cumulative] iteration costs allows to\nget performance improvements on problems with significantly different\ntime requirements per parallel loop iteration.\n\nOne of those problems is left multiplication with block-sparse matrix.\nUsing number of non-zero values per column block, we partition column\nblocks into contiguous sets with approximately equal number of\noperations to be performed.\n\nChange-Id: I4a862a10a586cdfbec22e8168a3423537039abc2\n",
  "tree_diff": [
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