4 papers
TopGQ: Fast GNN Post-Training Quantization Leveraging Topology Information
Dain Kwon, Kanghyun Choi, Hyeyoon Lee +4
Existing GNN quantization methods suffer from considerable quantization overhead, which severely limits their practical usage in real-world scenarios. To this end, we present TopGQ…
LOCALUT: Harnessing Capacity-Computation Tradeoffs for LUT-Based Inference in DRAM-PIM
Junguk Hong, Changmin Shin, Sukjin Kim +6
Lookup tables (LUTs) have recently gained attention as an alternative compute mechanism that maps input operands to precomputed results, eliminating the need for arithmetic logic.…
FlexiWalker: Extensible GPU Framework for Efficient Dynamic Random Walks with Runtime Adaptation
Seongyeon Park, Jaeyong Song, Changmin Shin +3
Dynamic random walks are fundamental to various graph analysis applications, offering advantages by adapting to evolving graph properties. Their runtime-dependent transition probab…
PathWeaver: A High-Throughput Multi-GPU System for Graph-Based Approximate Nearest Neighbor Search
Sukjin Kim, Seongyeon Park, Si Ung Noh +4
Graph-based Approximate Nearest Neighbor Search (ANNS) is widely adopted in numerous applications, such as recommendation systems, natural language processing, and computer vision.…