1 citations · 1 across the 1 of their papers we have counts for
5 papers
Uncovering the Memory Hierarchy of Modern NVIDIA GPUs for Accurate Simulation
Ziwen Wang, Jiapeng Zhou, Changxi Liu +2
Emerging artificial intelligence workloads, particularly Large Language Models (LLMs), place unprecedented demands on GPU memory systems. Consequently, architectural innovations in…
Scaling Shapley Energy Attribution to Large LLM Batches
Qi Luo, Ziwen Wang, Kunlin Li +2
LLM services have become essential infrastructure for applications such as chat assistants and coding agents. Service providers need to attribute resource consumption to individual…
Exploiting What NVIDIA Profilers Hide: Fast and Accurate Analytical GPU Performance Modeling
Ziwen Wang, Qi Luo, Kunlin Li +3
GPUs have become essential to many fields, including AI and scientific computing. As GPUs grow more complex, the design space of their hardware configurations becomes increasingly…
DGNA: Dissecting GPU NUMA Architecture through Microbenchmarking and Data Analysis
Changxi Liu, Yun Chen, Trevor E. Carlson
Graphics Processing Units (GPUs), due to their immense parallel processing capabilities, have become essential across various fields, including gaming and artificial intelligence.…
Pac-Sim: Simulation of Multi-threaded Workloads using Intelligent, Live Sampling
Changxi Liu, Alen Sabu, Akanksha Chaudhari +2
High-performance, multi-core processors are the key to accelerating workloads in several application domains. To continue to scale performance at the limit of Moore's Law and Denna…