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authorTim Rogers <[email protected]>2020-07-12 23:13:34 -0400
committerTim Rogers <[email protected]>2020-07-12 23:13:34 -0400
commit2e3856bc9b0979154c22b4650726bcfc5bfe1298 (patch)
treebc46859eecbef38f60067b7845b489bb6a524928
parent4192a5df8c400d9fc19d15a9eaca74191e45d08e (diff)
Updating the readme to get rid of the old arxiv paper and to instruct folks using 4.0 to cite the ISCA paper.
-rw-r--r--README.md15
1 files changed, 5 insertions, 10 deletions
diff --git a/README.md b/README.md
index 048fb3c..9a4dd69 100644
--- a/README.md
+++ b/README.md
@@ -11,12 +11,12 @@ This version of GPGPU-Sim has been tested with CUDA version 4.2,
Please see the copyright notice in the file COPYRIGHT distributed with this
release in the same directory as this file.
-If you use GPGPU-Sim in your research, please cite:
+If you use GPGPU-Sim 4.0 in your research, please cite:
-Ali Bakhoda, George Yuan, Wilson W. L. Fung, Henry Wong, Tor M. Aamodt,
-Analyzing CUDA Workloads Using a Detailed GPU Simulator, in IEEE International
-Symposium on Performance Analysis of Systems and Software (ISPASS), Boston, MA,
-April 19-21, 2009.
+Mahmoud Khairy, Zhesheng Shen, Tor M. Aamodt, Timothy G Rogers.
+Accel-Sim: An Extensible Simulation Framework for Validated GPU Modeling.
+In proceedings of the 47th IEEE/ACM International Symposium on Computer Architecture (ISCA),
+May 29 - June 3, 2020.
If you use cuDNN and Pytorch support, the Checkpoint function or the Debigging tool for functional simulation error in GPGPU-Sim for your research,
please cite:
@@ -24,11 +24,6 @@ Jonathan Lew, Deval Shah, Suchita Pati, Shaylin Cattell, Mengchi Zhang, Amruth S
Analyzing Machine Learning Workloads Using a Detailed GPU Simulator, arXiv:1811.08933,
https://arxiv.org/abs/1811.08933
-If you use the memory system in GPGPU-Sim, or the Volta/Pascal models,
-please cite:
-Mahmoud Khairy, Jain Akshay, Tor Aamodt, Timothy G Rogers,
-Exploring Modern GPU Memory System Design Challenges through Accurate Modeling, arXiv:1810.07269,
-https://arxiv.org/abs/1810.07269
If you use the Tensor Core in GPGPU-Sim or CUTLASS Library for your research
please cite: