4 papers
TileLens: Efficiently Using Large-Granularity Memory Systems with Transparent Two-Dimensional Memory Layout
Jae Hyung Ju, Euijun Chung, Hritvik Taneja +4
Large Language Model (LLM) inference is bottlenecked by the capacity and bandwidth of GPU High-Bandwidth Memory (HBM). Recent proposals, such as High-Bandwidth Flash (HBF) and RoMe…
Making Locality-aware GEMM Compatible with Page-Granularity Placement on Chiplet GPUs
Euijun Chung, Jae Hyung Ju, Hyesoon Kim
Multi-chiplet GPUs scale compute throughput and high-bandwidth memory (HBM) capacity, but their non-uniform memory system makes locality between chiplets and their data critical to…
Hardware vs. Software Implementation of Warp-Level Features in Vortex RISC-V GPU
Huanzhi Pu, Rishabh Ravi, Shinnung Jeong +5
RISC-V GPUs present a promising path for supporting GPU applications. Traditionally, GPUs achieve high efficiency through the SPMD (Single Program Multiple Data) programming model.…
Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems
Ayush Gundawar, Euijun Chung, Hyesoon Kim
The exponential growth of data-intensive machine learning workloads has exposed significant limitations in conventional GPU-accelerated systems, especially when processing datasets…