127 citations · 201 across the 8 of their papers we have counts for
9 papers
Skyplane: Optimizing Transfer Cost and Throughput Using Cloud-Aware Overlays
Paras Jain, Sam Kumar, Sarah Wooders +3
Cloud applications are increasingly distributing data across multiple regions and cloud providers. Unfortunately, wide-area bulk data transfers are often slow, bottlenecking applic…
Representing Long-Range Context for Graph Neural Networks with Global Attention
Zhanghao Wu, Paras Jain, Matthew A. Wright +3
Graph neural networks are powerful architectures for structured datasets. However, current methods struggle to represent long-range dependencies. Scaling the depth or width of GNNs…
Grounded Graph Decoding Improves Compositional Generalization in Question Answering
Yu Gai, Paras Jain, Wendi Zhang +3
Question answering models struggle to generalize to novel compositions of training patterns, such to longer sequences or more complex test structures. Current end-to-end models lea…
Accelerating Quadratic Optimization with Reinforcement Learning
Jeffrey Ichnowski, Paras Jain, Bartolomeo Stellato +6
First-order methods for quadratic optimization such as OSQP are widely used for large-scale machine learning and embedded optimal control, where many related problems must be rapid…
Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization
Paras Jain, Ajay Jain, Aniruddha Nrusimha +5
We formalize the problem of trading-off DNN training time and memory requirements as the tensor rematerialization optimization problem, a generalization of prior checkpointing stra…
Revec: Program Rejuvenation through Revectorization
Charith Mendis, Ajay Jain, Paras Jain +1
Modern microprocessors are equipped with Single Instruction Multiple Data (SIMD) or vector instructions which expose data level parallelism at a fine granularity. Programmers explo…