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cs.PL2026
Triton for MTIA: Bridging the Programming Model Gaps for Custom AI Accelerators
Haishan Zhu, Domi Yan, Michael Levesque-Dion +40
The rapid growth in machine learning workloads has fueled the proliferation of custom accelerator architectures. Designed from the ground up, these accelerators often expose progra…
cs.DC2026
Benchmarking Compound AI Applications for Hardware-Software Co-Design
Paramuth Samuthrsindh, Angel Cervantes, Varun Gohil +3
Compound AI applications, composed from interactions between Large Language Models (LLMs), Machine Learning (ML) models, external tools and data sources are quickly becoming an int…