amd/blis
1
0
Fork 0
mirror of https://github.com/amd/blis.git synced 2026-05-24 10:24:34 +00:00
Code Issues Packages Projects Releases Wiki Activity

Added SIAM/SC prize to "What's New" in README.md.

Browse Source
This commit is contained in:
Field G. Van Zee
2019-11-21 18:12:24 -06:00
parent 881b05ecd4
commit 05a4d583e6
1 changed files with 20 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
README.md
View File

@@ -93,6 +93,26 @@ all of which are available for free via the [edX platform](http://www.edx.org/).
What's New
----------
* **SIAM Activity Group Supercomputing Best Paper Prize for 2020** We are
thrilled to announce that the paper that we internally refer to as the second
BLIS paper,
"The BLIS Framework: Experiments in Portability." Field G. Van Zee, Tyler Smith, Bryan Marker, Tze Meng Low, Robert A. van de Geijn, Francisco Igual, Mikhail Smelyanskiy, Xianyi Zhang, Michael Kistler, Vernon Austel, John A. Gunnels, Lee Killough. ACM Transactions on Mathematical Software (TOMS), 42(2):12:1--12:19, 2016.
was selected for the [SIAM Activity Group on Supercomputing Best Paper Prize](https://www.siam.org/prizes-recognition/activity-group-prizes/detail/siag-sc-best-paper-prize)
for 2020. The prize is awarded once every two years to a paper judged to be
the most outstanding paper in the field of parallel scientific and engineering
computing, and has only been awarded once before (in 2016) since its inception
in 2015 (the committee did not award the prize in 2018). The prize will be
awarded at the [SIAM Conference on Parallel Processing for Scientific Computing](https://www.siam.org/conferences/cm/conference/pp20) in Seattle next February. Robert will
be present at the conference to accept the prize and give
[a talk on BLIS](https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=68266).
The selection committee sought to recognize the paper, "which validates BLIS,
a framework relying on the notion of microkernels that enables both productivity
and high performance." Their statement continues, "The framework will continue
having an important influence on the design and the instantiation of dense linear
algebra libraries."
* **Small/skinny matrix support for dgemm now available!** Thanks to
contributions made possible by our partnership with AMD, we have dramatically
accelerated `gemm` for double-precision real matrix problems where one or two