activity
20232026
collaborators

7 papers

cs.AI2026

Precision As You Need: Stochastic Computing Is a Dense Adaptive Quantizer

Haoran Jin, Kangqi Zhang, Jirong Yang +4

Matrix multiplications dominate the inference cost of modern transformer-based vision models, yet existing efficiency techniques such as post-training quantization and mixed-precis…

cs.AR2026

Fengshui: Demystifying Chiplet Ecosystem and Bespoke Neural Network Accelerator Codesign

Haoran Jin, Jirong Yang, Zhiheng Zhang +5

Modern ML workloads, with stringent latency and energy constraints, are increasingly hard to run efficiently on homogeneous commodity hardware. We argue that operator-level disaggr…

cs.AR2026

Rethinking Agentic Kernel Generation for Emerging Accelerators

Ruijie Gao, Jirong Yang, Barry Lyu +2

Emerging accelerators often lack mature compiler backends, motivating neural agents that generate and repair kernels from architectural documentation and simulator feedback. This a…

cs.AR2026

TensorLift: Automatic Extraction of Tensor-Level ISA Semantics from Accelerator RTL via MLIR Semantic Lifting

Ruijie Gao, Haoran Jin, Jirong Yang +1

Most proposed tensor accelerators lack well-documented ISAs and compiler backends, and are exercised only through hand-written kernels covering a handful of operators. Recent work…

astro-ph.IM2026

Compute System Organization for High Frequency High Order Wavefront Sensing and Control

Barry Lyu, Vaibhavi Manjarekar, Nathaniel Bleier

Maintaining long-term wavefront stability is critical for the Habitable Worlds Observatory (HWO), which targets contrasts approaching and therefore requires continuous d…

cs.AR2025

Mozart: A Chiplet Ecosystem-Accelerator Codesign Framework for Composable Bespoke Application Specific Integrated Circuits

Haoran Jin, Jirong Yang, Yunpeng Liu +3

Modern AI acceleration faces a fundamental challenge: conventional assumptions about memory requirements, batching effectiveness, and latency-throughput tradeoffs are systemwide ge…

cs.AR2023

Understanding Interactions Between Chip Architecture and Uncertainties in Semiconductor Supply and Demand

Ramakrishna Kanungo, Swamynathan Siva, Nathaniel Bleier +3

Mitigating losses from supply and demand volatility in the semiconductor supply chain and market has traditionally been cast as a logistics and forecasting problem. We investigate…