5 citations · 12 across the 17 of their papers we have counts for
9 papers · 1 filter
Learnable Low-Rank Polynomial Sketch for Effective Linear Attention
Zongyue Qin, Haoran Deng, Jason Cong +1
Softmax attention in Transformers suffers from quadratic complexity in sequence length, making it impractical for long-context applications. Linear attention alleviates this issue…
Can Agents Design Better Chips with a Higher Level Abstraction?
Zijian Ding, Yang Zou, Yizhou Sun +1
Large Language Model (LLM) agents are increasingly being explored for chip design, but most existing approaches operate directly at RTL. We ask whether agents can design better chi…
HarnessBridge: Learnable Bidirectional Controller for LLM Agent Harness
Xiaoxuan Wang, Haixin Wang, Alexander Taylor +3
Large language models are increasingly deployed as agents for long-horizon tasks, yet their performance is shaped not only by model capability and environment design, but also by t…
AgRefactor: Self-Evolving Agentic Workflow for HLS Compatibility and Performance
Yang Zou, Zijian Ding, Yizhou Sun +1
High-Level Synthesis (HLS) provides a fast path from concepts to silicon, but converting real-world software into synthesizable HLS code remains challenging due to restrictive lang…
AI+HW 2035: Shaping the Next Decade
Deming Chen, Jason Cong, Azalia Mirhoseini +27
Artificial intelligence (AI) and hardware (HW) are advancing at unprecedented rates, yet their trajectories have become inseparably intertwined. The global research community lacks…
Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference
Zifan He, Rui Ma, Yizhou Sun +1
Modern large language models (LLMs) increasingly depends on efficient long-context processing and generation mechanisms, including sparse attention, retrieval-augmented generation…
ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning
Xiaoxuan Wang, Han Zhang, Haixin Wang +11
Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interactive tasks. Despite encouraging ea…
FlexLLM: Composable HLS Library for Flexible Hybrid LLM Accelerator Design
Jiahao Zhang, Zifan He, Nicholas Fraser +3
We present FlexLLM, a composable High-Level Synthesis (HLS) library for rapid development of domain-specific LLM accelerators. FlexLLM exposes key architectural degrees of freedom…
Report for NSF Workshop on AI for Electronic Design Automation
Deming Chen, Vijay Ganesh, Weikai Li +7
This report distills the discussions and recommendations from the NSF Workshop on AI for Electronic Design Automation (EDA), held on December 10, 2024 in Vancouver alongside NeurIP…