90 citations · 229 across the 24 of their papers we have counts for
5 papers · 1 filter
STELLA: A 16nm Spatio-Temporal Elastic Low-Latency CGRA for Multi-Stage Pipelined Applications
Jun Yin, Chao Fang, Ryan Antonio +4
Emerging non-matrix ML kernels, such as LayerNorm, GeLu, FFT or circular convolutions, demand low-latency, energy-efficient spatial accelerators beyond MatMul-centric arrays. STELL…
ARES: Adaptive Reasoning-Effort Steering for PPA- and Cost-Aware RTL Optimization with LLM Agents
Stef Cuyckens, Mihaela Jivanescu, Jun Yin +2
Large language model (LLM) agents optimize the power, performance, and area (PPA) of register-transfer-level (RTL) designs by iterating over edits, synthesis, and PPA analysis, pay…
HiKV: Hierarchical Importance-Aware KV Cache with Hardware Acceleration for LLM Decoding
Chao Fang, Jun Yin, Man Shi +1
With the rapid adoption of long-context large language models (LLMs), the continuously growing KV cache during decoding has become the critical memory bottleneck. To tackle this ch…
CD-PIM: A High-Bandwidth and Compute-Efficient LPDDR5-Based PIM for Low-Batch LLM Acceleration on Edge-Device
Ye Lin, Chao Fang, Xiaoyong Song +4
Edge deployment of low-batch large language models (LLMs) faces critical memory bandwidth bottlenecks when executing memory-intensive general matrix-vector multiplications (GEMV) o…
A Scheduling Framework for Efficient MoE Inference on Edge GPU-NDP Systems
Qi Wu, Chao Fang, Jiayuan Chen +5
Mixture-of-Experts (MoE) models facilitate edge deployment by decoupling model capacity from active computation, yet their large memory footprint drives the need for GPU systems wi…