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20242026
most citedMLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI

3 citations · 3 across the 9 of their papers we have counts for

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cs.CR2025

Rigorous Evaluation of Microarchitectural Side-Channels with Statistical Model Checking

Weihang Li, Pete Crowley, Arya Tschand +3

Rigorous quantitative evaluation of microarchitectural side channels is challenging for two reasons. First, the processors, attacks, and defenses often exhibit probabilistic behavi…

cs.AR2025

QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture

Shvetank Prakash, Andrew Cheng, Mark Mazumder +24

The field of computer architecture, which bridges high-level software abstractions and low-level hardware implementations, remains absent from current large language model (LLM) ev…

cs.AR2025

Lifetime-Aware Design for Item-Level Intelligence at the Extreme Edge

Shvetank Prakash, Andrew Cheng, Olof Kindgren +13

We present FlexiFlow, a lifetime-aware design framework for item-level intelligence (ILI) where computation is integrated directly into disposable products like food packaging and…

cs.DC2025

SwizzlePerf: Hardware-Aware LLMs for GPU Kernel Performance Optimization

Arya Tschand, Muhammad Awad, Ryan Swann +5

Large language models (LLMs) have shown progress in GPU kernel performance engineering using inefficient search-based methods that optimize around runtime. Any existing approach la…

cs.AR2025

QuArch: A Question-Answering Dataset for AI Agents in Computer Architecture

Shvetank Prakash, Andrew Cheng, Jason Yik +14

We introduce QuArch, a dataset of 1500 human-validated question-answer pairs designed to evaluate and enhance language models' understanding of computer architecture. The dataset c…