1 citations · 1 across the 4 of their papers we have counts for
5 papers
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…
A 16 nm 1.60TOPS/W High Utilization DNN Accelerator with 3D Spatial Data Reuse and Efficient Shared Memory Access
Xiaoling Yi, Ryan Antonio, Yunhao Deng +4
Achieving high compute utilization across a wide range of AI workloads is crucial for the efficiency of versatile DNN accelerators. This paper presents the Voltra chip and its util…
ACCO: Automated Causal CNN Scheduling Optimizer for Real-Time Edge Accelerators
Jun Yin, Linyan Mei, Andre Guntoro +1
Spatio-Temporal Convolutional Neural Networks (ST-CNN) allow extending CNN capabilities from image processing to consecutive temporal-pattern recognition. Generally, state-of-the-a…