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cs.AR2026

KernelCraft: Benchmarking for Agentic Close-to-Metal Kernel Generation on Emerging Hardware

Jiayi Nie, Haoran Wu, Yao Lai +9

New AI accelerators with novel instruction set architectures (ISAs) often require developers to manually craft low-level kernels, a time-consuming and error-prone process that does…

cs.AR2026

NPU Design for Diffusion Language Model Inference

Binglei Lou, Haoran Wu, Kevin Lau +9

Diffusion-based LLMs (dLLMs) fundamentally depart from traditional autoregressive (AR) LLM inference: they leverage bidirectional attention, block-wise KV cache refreshing, cross-s…

cs.AR2026

MemExplorer: Navigating the Heterogeneous Memory Design Space for Agentic Inference NPUs

Haoran Wu, Zeyu Cao, Yao Lai +15

Emerging agentic LLM workloads are driving rapidly growing demand on both memory capacity and bandwidth, with different phases of inference (e.g., prefill and decode) imposing dist…

cs.AR2026

Combating the Memory Walls: Optimization Pathways for Long-Context Agentic LLM Inference

Haoran Wu, Can Xiao, Jiayi Nie +15

LLMs now form the backbone of AI agents across a diverse range of applications, including tool use, command-line interfaces, and web or computer interaction. These agentic LLM infe…

cs.AR2025

ASPO: Constraint-Aware Bayesian Optimization for FPGA-based Soft Processors

Haoran Wu, Ce Guo, Wayne Luk +1

Bayesian Optimization (BO) has shown promise in tuning processor design parameters. However, standard BO does not support constraints involving categorical parameters such as types…