18 citations · 22 across the 4 of their papers we have counts for
4 papers
SOLAR: AI-Powered Speed-of-Light Performance Analysis
Qijing Huang, Sana Damani, Zhifan Ye +9
How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to software, hardware, and algorithm…
SYMI: Efficient Mixture-of-Experts Training via Model and Optimizer State Decoupling
Athinagoras Skiadopoulos, Mark Zhao, Swapnil Gandhi +3
Mixture-of-Experts (MoE) models have become a widely-adopted solution to continue scaling model sizes without a corresponding linear increase in compute. During MoE model training,…
ReCycle: Resilient Training of Large DNNs using Pipeline Adaptation
Swapnil Gandhi, Mark Zhao, Athinagoras Skiadopoulos +1
Training large Deep Neural Network (DNN) models requires thousands of GPUs over the course of several days or weeks. At this scale, failures are frequent and can have a big impact…
Apiary: A DBMS-Integrated Transactional Function-as-a-Service Framework
Peter Kraft, Qian Li, Kostis Kaffes +16
Developers increasingly use function-as-a-service (FaaS) platforms for data-centric applications that perform low-latency and transactional operations on data, such as for microser…