1 citations · 1 across the 1 of their papers we have counts for
5 papers
LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme
Jeongmin Brian Park, Kun Wu, Vikram Sharma Mailthody +3
Graph Neural Networks (GNNs) are widely used today in recommendation systems, fraud detection, and node/link classification tasks. Real world GNNs continue to scale in size and req…
Characterizing Adaptive Mesh Refinement on Heterogeneous Platforms with Parthenon-VIBE
Akash Poptani, Alireza Khadem, Scott Mahlke +3
Hero-class HPC simulations rely on Adaptive Mesh Refinement (AMR) to reduce compute and memory demands while maintaining accuracy. This work analyzes the performance of Parthenon,…
Strata: Hierarchical Context Caching for Long Context Language Model Serving
Zhiqiang Xie, Ziyi Xu, Mark Zhao +5
Large Language Models (LLMs) with expanding context windows face significant performance hurdles. While caching key-value (KV) states is critical for avoiding redundant computation…
DX100: A Programmable Data Access Accelerator for Indirection
Alireza Khadem, Kamalavasan Kamalakkannan, Zhenyan Zhu +8
Indirect memory accesses frequently appear in applications where memory bandwidth is a critical bottleneck. Prior indirect memory access proposals, such as indirect prefetchers, ru…
Multi-Dimensional Vector ISA Extension for Mobile In-Cache Computing
Alireza Khadem, Daichi Fujiki, Hilbert Chen +4
In-cache computing technology transforms existing caches into long-vector compute units and offers low-cost alternatives to building expensive vector engines for mobile CPUs. Unfor…