4 papers · 1 filter
SNAC-Pack 2.0: Scaled-Out Surrogate Neural Architecture Codesign
Jason Weitz, Dmitri Demler, Benjamin Hawks +3
Neural architecture search (NAS) is a powerful approach for automating model design, but existing methods often optimize for accuracy alone or rely on proxy metrics such as bit ope…
wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation
Benjamin Hawks, Jason Weitz, Dmitri Demler +13
As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantl…
An MLCommons Scientific Benchmarks Ontology
Ben Hawks, Gregor von Laszewski, Matthew D. Sinclair +6
Scientific machine learning research spans diverse domains and data modalities, yet existing benchmark efforts remain siloed and lack standardization. This makes novel and transfor…
Reliable edge machine learning hardware for scientific applications
Tommaso Baldi, Javier Campos, Ben Hawks +15
Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementatio…