arXiv:2607. 18069v1 Announce Type: cross Abstract: As more capable AI models are increasingly integrated into critical computer systems, the lack of control over AI intent motivates safety mechanisms.
By Haiyue Ma, Lauren Malek, Joseph Forzani, David Wentzlaff
arXiv:2209. 00188v4 Announce Type: replace-cross Abstract: Long-latency load requests continue to limit the performance of high-performance processors.
By Rahul Bera, Konstantinos Kanellopoulos, Shankar Balachandran, David Novo, Ataberk Olgun, Mohammad Sadrosadati, Onur Mutlu
arXiv:2608. 09874v1 Announce Type: new Abstract: Agentic artificial intelligence has shown great promise in automating algorithm design, but scaling similar techniques to computer microarchitecture discovery remains challenging due to vast search spaces, strict hardware budgets, and long simulation times.
By Abraham Gonzalez, Raghav Gupta, Akanksha Jain, Hanna Alam, Alexander Novikov, Po-Sen Huang, Matej Balog, Marvin Eisenberger, Sergey Shirobokov, Ng\^an V\~u, Hank Levy, Borivoje Nikoli\'c, Sagar Karandikar, Martin Dixon, Parthasarathy Ranganathan
arXiv:2606. 14716v1 Announce Type: cross Abstract: Edge object detection on embedded hardware requires balancing inference latency and detection quality under changing resource pressure.
By Kushal Khemani, Evan Leri, George Xu, Amit Hod
arXiv:2607. 03876v1 Announce Type: new Abstract: With the rise of small quantized GGUF-based language models and their increasing use for on-device inference tasks, we have seen the growing need for an approach capable of reliably delivering these models at scale even under severe memory bandwidth constraints such as those imposed by pure CPU implementations.
By Sadra Saremi
arXiv:2504. 11320v4 Announce Type: replace-cross Abstract: Large language models now serve millions of users daily, with providers incurring costs exceeding $700,000 per day.
By Ruicheng Ao, Gan Luo, David Simchi-Levi, Xinshang Wang