3 citations · 7 across the 10 of their papers we have counts for
4 papers · 1 filter
Design Space Exploration of DMA based Finer-Grain Compute Communication Overlap
Shagnik Pal, Shaizeen Aga, Suchita Pati +2
Modern ML workloads demand distributing training and inference across multiple GPUs. However, these parallelization techniques often suffer from exposed critical-path communication…
DMA-Latte: Expanding the Reach of DMA Offloads to Latency-bound ML Communication
Suchita Pati, Shaizeen Aga, Mahzabeen Islam +3
Offloading communication to existing direct memory access (DMA) engines, available on most state-of-the-art commercial GPUs, has emerged as a practical and low-cost solution to eff…
SeqPoint: Identifying Representative Iterations of Sequence-based Neural Networks
Suchita Pati, Shaizeen Aga, Matthew D. Sinclair +1
The ubiquity of deep neural networks (DNNs) continues to rise, making them a crucial application class for hardware optimizations. However, detailed profiling and characterization…
Analyzing Machine Learning Workloads Using a Detailed GPU Simulator
Jonathan Lew, Deval Shah, Suchita Pati +8
Most deep neural networks deployed today are trained using GPUs via high-level frameworks such as TensorFlow and PyTorch. This paper describes changes we made to the GPGPU-Sim simu…