16 citations · 19 across the 5 of their papers we have counts for
3 papers · 1 filter
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…
Specializing Coherence, Consistency, and Push/Pull for GPU Graph Analytics
Giordano Salvador, Wesley H. Darvin, Muhammad Huzaifa +3
This work provides the first study to explore the interaction of update propagation with and without fine-grained synchronization (push vs. pull), emerging coherence protocols (GPU…
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…