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20212026
most citedPerformance Evaluation of Python Parallel Programming Models: Charm4Py and mpi4py

13 citations · 14 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2026

OpenAttention: One Percent Is Enough with Tail Proxies

Hyunwoo Yu, Jongbeom Lee, Hyunbin Kim +8

Sparse attention reads only a small subset of the key-value cache, and how to treat the unread tail remains a key challenge. Discarding the tail biases the output, and sampling it…

cs.CV2026

SparSTAR: Sparse Attention for SpaceTime AutoRegressive Video Synthesis

Jongbeom Lee, Hyunwoo Yu, Jincheol Yang +2

InfinityStar extends visual autoregressive generation to video through a sequence of image and clip pyramids. Its changing scale and cross-clip context, however, leave late-scale a…

cs.LO2023★ 1 cited

Formal Verification of Chase-Lev Deque in Concurrent Separation Logic

Jaemin Choi

Chase-Lev deque is a concurrent data structure designed for efficient load balancing in multiprocessor scheduling. It employs a work-stealing strategy, where each thread possesses…

cs.DC2022

Improving Scalability with GPU-Aware Asynchronous Tasks

Jaemin Choi, David F. Richards, Laxmikant V. Kale

Asynchronous tasks, when created with over-decomposition, enable automatic computation-communication overlap which can substantially improve performance and scalability. This is no…

cs.DC2021★ 13 cited

Performance Evaluation of Python Parallel Programming Models: Charm4Py and mpi4py

Zane Fink, Simeng Liu, Jaemin Choi +2

Python is rapidly becoming the lingua franca of machine learning and scientific computing. With the broad use of frameworks such as Numpy, SciPy, and TensorFlow, scientific computi…

cs.DC2021

Accelerating Communication for Parallel Programming Models on GPU Systems

Jaemin Choi, Zane Fink, Sam White +3

As an increasing number of leadership-class systems embrace GPU accelerators in the race towards exascale, efficient communication of GPU data is becoming one of the most critical…