Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

fixed a mistake in the calculate_total_cols kernels. #295

Merged
merged 1 commit into from
Apr 24, 2019
Merged

fixed a mistake in the calculate_total_cols kernels. #295

merged 1 commit into from
Apr 24, 2019

Conversation

fritzgoebel
Copy link
Collaborator

For big matrices this had the consequence of an illegal memory access since there was not enough memory allocated for the sellp matrix.

@hartwiganzt hartwiganzt requested a review from thoasm April 24, 2019 13:10
thoasm
thoasm approved these changes Apr 24, 2019
View reviewed changes
Copy link
Member

@thoasm thoasm left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM, good catch!

@thoasm thoasm added is:bug Something looks wrong. mod:cuda This is related to the CUDA module. type:matrix-format This is related to the Matrix formats labels Apr 24, 2019
@thoasm thoasm merged commit fe58c94 into ginkgo-project:develop Apr 24, 2019
tcojean added a commit that referenced this pull request Oct 20, 2019
@tcojean
Merge Release v1.1.0
b9bec82 
The Ginkgo team is proud to announce the new minor release of Ginkgo version
1.1.0. This release brings several performance improvements, adds Windows support, 
adds support for factorizations inside Ginkgo and a new ILU preconditioner
based on ParILU algorithm, among other things. For detailed information, check the respective issue.

Supported systems and requirements:
+ For all platforms, cmake 3.9+
+ Linux and MacOS
  + gcc: 5.3+, 6.3+, 7.3+, 8.1+
  + clang: 3.9+
  + Intel compiler: 2017+
  + Apple LLVM: 8.0+
  + CUDA module: CUDA 9.0+
+ Windows
  + MinGW and CygWin: gcc 5.3+, 6.3+, 7.3+, 8.1+
  + Microsoft Visual Studio: VS 2017 15.7+
  + CUDA module: CUDA 9.0+, Microsoft Visual Studio
  + OpenMP module: MinGW or CygWin.


The current known issues can be found in the [known issues
page](https://github.com/ginkgo-project/ginkgo/wiki/Known-Issues).


Additions:
+ Upper and lower triangular solvers ([#327](#327), [#336](#336), [#341](#341), [#342](#342)) 
+ New factorization support in Ginkgo, and addition of the ParILU
  algorithm ([#305](#305), [#315](#315), [#319](#319), [#324](#324))
+ New ILU preconditioner ([#348](#348), [#353](#353))
+ Windows MinGW and Cygwin support ([#347](#347))
+ Windows Visual studio support ([#351](#351))
+ New example showing how to use ParILU as a preconditioner ([#358](#358))
+ New example on using loggers for debugging ([#360](#360))
+ Add two new 9pt and 27pt stencil examples ([#300](#300), [#306](#306))
+ Allow benchmarking CuSPARSE spmv formats through Ginkgo's benchmarks ([#303](#303))
+ New benchmark for sparse matrix format conversions ([#312](#312))
+ Add conversions between CSR and Hybrid formats ([#302](#302), [#310](#310))
+ Support for sorting rows in the CSR format by column idices ([#322](#322))
+ Addition of a CUDA COO SpMM kernel for improved performance ([#345](#345))
+ Addition of a LinOp to handle perturbations of the form (identity + scalar *
  basis * projector) ([#334](#334))
+ New sparsity matrix representation format with Reference and OpenMP
  kernels ([#349](#349), [#350](#350))

Fixes:
+ Accelerate GMRES solver for CUDA executor ([#363](#363))
+ Fix BiCGSTAB solver convergence ([#359](#359))
+ Fix CGS logging by reporting the residual for every sub iteration ([#328](#328))
+ Fix CSR,Dense->Sellp conversion's memory access violation ([#295](#295))
+ Accelerate CSR->Ell,Hybrid conversions on CUDA ([#313](#313), [#318](#318))
+ Fixed slowdown of COO SpMV on OpenMP ([#340](#340))
+ Fix gcc 6.4.0 internal compiler error ([#316](#316))
+ Fix compilation issue on Apple clang++ 10 ([#322](#322))
+ Make Ginkgo able to compile on Intel 2017 and above ([#337](#337))
+ Make the benchmarks spmv/solver use the same matrix formats ([#366](#366))
+ Fix self-written isfinite function ([#348](#348))
+ Fix Jacobi issues shown by cuda-memcheck

Tools and ecosystem:
+ Multiple improvements to the CI system and tools ([#296](#296), [#311](#311), [#365](#365))
+ Multiple improvements to the Ginkgo containers ([#328](#328), [#361](#361))
+ Add sonarqube analysis to Ginkgo ([#304](#304), [#308](#308), [#309](#309))
+ Add clang-tidy and iwyu support to Ginkgo ([#298](#298))
+ Improve Ginkgo's support of xSDK M12 policy by adding the `TPL_` arguments
  to CMake ([#300](#300))
+ Add support for the xSDK R7 policy ([#325](#325))
+ Fix examples in html documentation ([#367](#367))
tcojean added a commit that referenced this pull request Oct 21, 2019
@tcojean
Merge Release v1.1.0 for develop
20823e7 
The Ginkgo team is proud to announce the new minor release of Ginkgo version
1.1.0. This release brings several performance improvements, adds Windows support,
adds support for factorizations inside Ginkgo and a new ILU preconditioner
based on ParILU algorithm, among other things. For detailed information, check the respective issue.

Supported systems and requirements:
+ For all platforms, cmake 3.9+
+ Linux and MacOS
  + gcc: 5.3+, 6.3+, 7.3+, 8.1+
  + clang: 3.9+
  + Intel compiler: 2017+
  + Apple LLVM: 8.0+
  + CUDA module: CUDA 9.0+
+ Windows
  + MinGW and Cygwin: gcc 5.3+, 6.3+, 7.3+, 8.1+
  + Microsoft Visual Studio: VS 2017 15.7+
  + CUDA module: CUDA 9.0+, Microsoft Visual Studio
  + OpenMP module: MinGW or Cygwin.


The current known issues can be found in the [known issues
page](https://github.com/ginkgo-project/ginkgo/wiki/Known-Issues).


### Additions
+ Upper and lower triangular solvers ([#327](#327), [#336](#336), [#341](#341), [#342](#342)) 
+ New factorization support in Ginkgo, and addition of the ParILU
  algorithm ([#305](#305), [#315](#315), [#319](#319), [#324](#324))
+ New ILU preconditioner ([#348](#348), [#353](#353))
+ Windows MinGW and Cygwin support ([#347](#347))
+ Windows Visual Studio support ([#351](#351))
+ New example showing how to use ParILU as a preconditioner ([#358](#358))
+ New example on using loggers for debugging ([#360](#360))
+ Add two new 9pt and 27pt stencil examples ([#300](#300), [#306](#306))
+ Allow benchmarking CuSPARSE spmv formats through Ginkgo's benchmarks ([#303](#303))
+ New benchmark for sparse matrix format conversions ([#312](#312))
+ Add conversions between CSR and Hybrid formats ([#302](#302), [#310](#310))
+ Support for sorting rows in the CSR format by column idices ([#322](#322))
+ Addition of a CUDA COO SpMM kernel for improved performance ([#345](#345))
+ Addition of a LinOp to handle perturbations of the form (identity + scalar *
  basis * projector) ([#334](#334))
+ New sparsity matrix representation format with Reference and OpenMP
  kernels ([#349](#349), [#350](#350))

### Fixes
+ Accelerate GMRES solver for CUDA executor ([#363](#363))
+ Fix BiCGSTAB solver convergence ([#359](#359))
+ Fix CGS logging by reporting the residual for every sub iteration ([#328](#328))
+ Fix CSR,Dense->Sellp conversion's memory access violation ([#295](#295))
+ Accelerate CSR->Ell,Hybrid conversions on CUDA ([#313](#313), [#318](#318))
+ Fixed slowdown of COO SpMV on OpenMP ([#340](#340))
+ Fix gcc 6.4.0 internal compiler error ([#316](#316))
+ Fix compilation issue on Apple clang++ 10 ([#322](#322))
+ Make Ginkgo able to compile on Intel 2017 and above ([#337](#337))
+ Make the benchmarks spmv/solver use the same matrix formats ([#366](#366))
+ Fix self-written isfinite function ([#348](#348))
+ Fix Jacobi issues shown by cuda-memcheck

### Tools and ecosystem improvements
+ Multiple improvements to the CI system and tools ([#296](#296), [#311](#311), [#365](#365))
+ Multiple improvements to the Ginkgo containers ([#328](#328), [#361](#361))
+ Add sonarqube analysis to Ginkgo ([#304](#304), [#308](#308), [#309](#309))
+ Add clang-tidy and iwyu support to Ginkgo ([#298](#298))
+ Improve Ginkgo's support of xSDK M12 policy by adding the `TPL_` arguments
  to CMake ([#300](#300))
+ Add support for the xSDK R7 policy ([#325](#325))
+ Fix examples in html documentation ([#367](#367))


Related PR: #370
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Reviewers

@thoasm thoasm thoasm approved these changes

@hartwiganzt hartwiganzt hartwiganzt approved these changes

Assignees
No one assigned
Labels
is:bug Something looks wrong. mod:cuda This is related to the CUDA module. type:matrix-format This is related to the Matrix formats
Projects
None yet
Milestone
No milestone
Development

Successfully merging this pull request may close these issues.
3 participants
@fritzgoebel @thoasm @hartwiganzt