3 citations · 3 across the 9 of their papers we have counts for
10 papers
Rethinking Heterogeneous System Disaggregation for Subquadratic Attention
Arya Tschand, Yaosheng Fu, Vikram Sharma Mailthody +6
Frontier language models are more aggressively using subquadratic attention to reduce the memory footprint and compute requirements during inference while still delivering frontier…
ArchEval: Measuring AI Agents as Computer Architects
Chenyu Wang, Zishen Wan, Jeffrey Ma +8
Computer architecture has long used benchmarks to make progress measurable. LLM agents create a different measurement problem: success is not merely writing code or tuning paramete…
JAXBench: Benchmarking Autonomous TPU Kernel Optimization
Arya Tschand, Charles Hong, Julian Walker +7
Rigorous benchmarks have driven progress in autonomous GPU kernel performance optimization by establishing a shared target to hillclimb on, but no equivalent exists for TPUs. We pr…
GenAI for Systems: Recurring Challenges and Design Principles from Software to Silicon
Arya Tschand, Chenyu Wang, Zishen Wan +21
Generative AI is reshaping how computing systems are designed, optimized, and built, yet research remains fragmented across software, architecture, and chip design communities. Thi…
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…
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…
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…
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…
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…
MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI
Arya Tschand, Arun Tejusve Raghunath Rajan, Sachin Idgunji +23
Rapid adoption of machine learning (ML) technologies has led to a surge in power consumption across diverse systems, from tiny IoT devices to massive datacenter clusters. Benchmark…