5 papers
Duplication-Aware Retiming and Cell Interface Redesign for Superconductor Circuit Minimization
Panagiotis Papanikolaou, Alex Vanasse, Haoran Jin +2
Superconductor electronics have increasingly shifted away from RSFQ and its variants toward logic families that eliminate explicit gate-level clocking. While this transition enable…
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…
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…
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…
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…