3 citations · 6 across the 16 of their papers we have counts for
5 papers · 1 filter
Optimizing ML Concurrent Computation and Communication with GPU DMA Engines
Anirudha Agrawal, Shaizeen Aga, Suchita Pati +1
Concurrent computation and communication (C3) is a pervasive paradigm in ML and other domains, making its performance optimization crucial. In this paper, we carefully characterize…
FinGraV: Methodology for Fine-Grain GPU Power Visibility and Insights
Varsha Singhania, Shaizeen Aga, Mohamed Assem Ibrahim
Ubiquity of AI makes optimizing GPU power a priority as large GPU-based clusters are often employed to train and serve AI models. An important first step in optimizing GPU power co…
Global Optimizations & Lightweight Dynamic Logic for Concurrency
Suchita Pati, Shaizeen Aga, Nuwan Jayasena +1
Modern accelerators like GPUs are increasingly executing independent operations concurrently to improve the device's compute utilization. However, effectively harnessing it on GPUs…
Balanced Data Placement for GEMV Acceleration with Processing-In-Memory
Mohamed Assem Ibrahim, Mahzabeen Islam, Shaizeen Aga
With unprecedented demand for generative AI (GenAI) inference, acceleration of primitives that dominate GenAI such as general matrix-vector multiplication (GEMV) is receiving consi…
T3: Transparent Tracking & Triggering for Fine-grained Overlap of Compute & Collectives
Suchita Pati, Shaizeen Aga, Mahzabeen Islam +2
Large Language Models increasingly rely on distributed techniques for their training and inference. These techniques require communication across devices which can reduce scaling e…