1 citations · 1 across the 3 of their papers we have counts for
3 papers
Integrated Hardware Architecture and Device Placement Search
Irene Wang, Jakub Tarnawski, Amar Phanishayee +1
Distributed execution of deep learning training involves a dynamic interplay between hardware accelerator architecture and device placement strategy. This is the first work to expl…
Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training
Muhammad Adnan, Amar Phanishayee, Janardhan Kulkarni +2
In this paper, we present a novel technique to search for hardware architectures of accelerators optimized for end-to-end training of deep neural networks (DNNs). Our approach addr…
DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving
Foteini Strati, Sara Mcallister, Amar Phanishayee +2
Distributed LLM serving is costly and often underutilizes hardware accelerators due to three key challenges: bubbles in pipeline-parallel deployments caused by the bimodal latency…