1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2021★ 1 cited
ECRM: Efficient Fault Tolerance for Recommendation Model Training via Erasure Coding
Kaige Liu, Jack Kosaian, K. V. Rashmi
Deep-learning-based recommendation models (DLRMs) are widely deployed to serve personalized content to users. DLRMs are large in size due to their use of large embedding tables, an…
cs.DC2019
Parity Models: A General Framework for Coding-Based Resilience in ML Inference
Jack Kosaian, K. V. Rashmi, Shivaram Venkataraman
Machine learning models are becoming the primary workhorses for many applications. Production services deploy models through prediction serving systems that take in queries and ret…
cs.LG2018
Learning a Code: Machine Learning for Approximate Non-Linear Coded Computation
Jack Kosaian, K. V. Rashmi, Shivaram Venkataraman
Machine learning algorithms are typically run on large scale, distributed compute infrastructure that routinely face a number of unavailabilities such as failures and temporary slo…