@Techmeme@techhub.socialSources: Anduril has begun exploring the possibility of establishing operations in Israel and is in talks to recruit a local manager (Sophie Shulman/CTech)
https://www.calcalistech.com/ctechnews/article/hj75fpszgl
@arXiv_csAR_bot@mastoxiv.pageWhy Do Prefetchers Fail? Let Agents Answer
Xiangfeng Sun, Ceyu Xu, Ningzhi Ai, Zeyu Zhu, Yiyang Yuan, Yuan Xie
https://arxiv.org/abs/2608.13027 https://arxiv.org/pdf/2608.13027 https://arxiv.org/html/2608.13027
arXiv:2608.13027v1 Announce Type: new
Abstract: Hardware prefetchers are crucial to processor performance, yet their design remains labor-intensive and expert-driven. Architects inspect execution and memory-access traces, identify patterns, translate them into online hardware heuristics, and evaluate them in simulation, often with no guarantee of improvement. Human experts cannot systematically inspect billion-instruction traces across diverse real-world workloads.
We present a performance-anomaly-driven autoresearch flow that repeatedly asks why a deployed prefetcher fails and uses the diagnoses to construct the Mixture of Prefetchers (MoP). Each iteration localizes high-impact unexplained misses to program counters, gives agents hardware logs, source code, and sliced traces, validates diagnoses through runnable minimal cases, and synthesizes specialized sub-prefetchers for recurring pattern families. Measured performance and remaining anomalies feed subsequent iterations, enabling simulator-in-the-loop discovery beyond model priors.
The campaign consumes 1.91 billion DeepSeek V4 Pro tokens. On SPEC CPU2006 and SPEC CPU2017, MoP achieves a 61.1% geomean IPC speedup over no prefetching, outperforming the human-designed Alecto, Berti, and Pythia prefetchers by 14.5%, 21.6%, and 23.6%, respectively. RTL synthesis in a 6nm library reports 110 KB of on-chip storage and 0.0347 mm^2 area. To our knowledge, this is the first empirical demonstration that an agent-driven hardware-design process can produce an RTL-practical prefetcher that outperforms state-of-the-art human designs on unseen workloads.
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