Skip to content

GitLab

  • Menu
Projects Groups Snippets
  • Help
    • Help
    • Support
    • Community forum
    • Submit feedback
    • Contribute to GitLab
  • Sign in
  • tnl-dev tnl-dev
  • Project information
    • Project information
    • Activity
    • Labels
    • Members
  • Repository
    • Repository
    • Files
    • Commits
    • Branches
    • Tags
    • Contributors
    • Graph
    • Compare
  • Issues 36
    • Issues 36
    • List
    • Boards
    • Service Desk
    • Milestones
  • Merge requests 4
    • Merge requests 4
  • Deployments
    • Deployments
    • Releases
  • Analytics
    • Analytics
    • Value stream
    • Repository
  • Snippets
    • Snippets
  • Activity
  • Graph
  • Create a new issue
  • Commits
  • Issue Boards
Collapse sidebar
  • TNL
  • tnl-devtnl-dev
  • Issues
  • #91

Closed
Open
Created Sep 28, 2021 by Jakub Klinkovský@klinkovskyOwner

Segments: "compute" parameter is not checked always

  • BiEllpack: compute seems to be checked correctly
  • ChunkedEllpack: compute seems to be checked correctly
  • Ellpack: compute is checked only in the general cases (1, 2), but not in the CUDA specializations (3, 4)
  • SlicedEllpack: compute is not checked at all: 1, 2
  • CSR:
    • Adaptive: compute is not checked: 1
    • Hybrid: compute is checked in the multivector kernel, but not in the hybrid kernel
    • Light: compute is checked in the multivector kernel, but not in the other kernels
    • Scalar: compute seems to be checked correctly
    • Vector: compute is not checked: 1

Obviously we don't have any tests for this feature. But do we have some benchmark which proves that this optimization helps in some cases?

Assignee
Assign to
Time tracking