152 citations · 187 across the 5 of their papers we have counts for
8 papers
SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills
Amey Agrawal, Ashish Panwar, Jayashree Mohan +3
Large Language Model (LLM) inference consists of two distinct phases - prefill phase which processes the input prompt and decode phase which generates output tokens autoregressivel…
Synergy: Resource Sensitive DNN Scheduling in Multi-Tenant Clusters
Jayashree Mohan, Amar Phanishayee, Janardhan Kulkarni +1
Training Deep Neural Networks (DNNs) is a widely popular workload in both enterprises and cloud data centers. Existing schedulers for DNN training consider GPU as the dominant reso…
Memory Optimization for Deep Networks
Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan +2
Deep learning is slowly, but steadily, hitting a memory bottleneck. While the tensor computation in top-of-the-line GPUs increased by 32x over the last five years, the total availa…
Analyzing and Mitigating Data Stalls in DNN Training
Jayashree Mohan, Amar Phanishayee, Ashish Raniwala +1
Training Deep Neural Networks (DNNs) is resource-intensive and time-consuming. While prior research has explored many different ways of reducing DNN training time, the impact of in…
RECIPE : Converting Concurrent DRAM Indexes to Persistent-Memory Indexes
Se Kwon Lee, Jayashree Mohan, Sanidhya Kashyap +2
We present Recipe, a principled approach for converting concurrent DRAM indexes into crash-consistent indexes for persistent memory (PM). The main insight behind Recipe is that iso…
Analyzing GDPR Compliance Through the Lens of Privacy Policy
Jayashree Mohan, Melissa Wasserman, Vijay Chidambaram
With the arrival of the European Union's General Data Protection Regulation (GDPR), several companies are making significant changes to their systems to achieve compliance. The cha…