171 citations · 350 across the 38 of their papers we have counts for
12 papers · 1 filter
SwiftFusion: Scalable Sequence Parallelism for Distributed Inference of Diffusion Transformers on GPUs
Jiacheng Yang, Jun Wu, Yaoyao Ding +3
Diffusion Transformers (DiTs) have gained increasing adoption in high-quality image and video generation. As demand for higher-resolution images and longer videos increases, single…
Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization
Zhanda Zhu, Christina Giannoula, Muralidhar Andoorveedu +4
Various parallelism, such as data, tensor, and pipeline parallelism, along with memory optimizations like activation checkpointing, redundancy elimination, and offloading, have bee…
Seesaw: High-throughput LLM Inference via Model Re-sharding
Qidong Su, Wei Zhao, Xin Li +6
To improve the efficiency of distributed large language model (LLM) inference, various parallelization strategies, such as tensor and pipeline parallelism, have been proposed. Howe…
Tally: Non-Intrusive Performance Isolation for Concurrent Deep Learning Workloads
Wei Zhao, Anand Jayarajan, Gennady Pekhimenko
GPU underutilization is a significant concern in many production deep learning clusters, leading to prolonged job queues and increased operational expenses. A promising solution to…
Minuet: Accelerating 3D Sparse Convolutions on GPUs
Jiacheng Yang, Christina Giannoula, Jun Wu +3
Sparse Convolution (SC) is widely used for processing 3D point clouds that are inherently sparse. Different from dense convolution, SC preserves the sparsity of the input point clo…
HybridTier: an Adaptive and Lightweight CXL-Memory Tiering System
Kevin Song, Jiacheng Yang, Zixuan Wang +3
Modern workloads are demanding increasingly larger memory capacity. Compute Express Link (CXL)-based memory tiering has emerged as a promising solution for addressing this problem…