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@@ -18,15 +18,23 @@ 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. +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: +Jonathan Lew, Deval Shah, Suchita Pati, Shaylin Cattell, Mengchi Zhang, Amruth Sandhupatla, Christopher Ng, Negar Goli, Matthew D. Sinclair, Timothy G. Rogers, Tor M. Aamodt +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 tensorcore in GPGPU-Sim or CUTLASS Library in your research +If you use the Tensor Core in GPGPU-Sim or CUTLASS Library for your research please cite: - add the arxiv link here +Md Aamir Raihan, Negar Goli, Tor Aamodt, +Modeling Deep Learning Accelerator Enabled GPUs, arXiv:1811.08309, +https://arxiv.org/abs/1811.08309 If you use the GPUWattch energy model in your research, please cite: |