8 citations · 9 across the 4 of their papers we have counts for
3 papers · 1 filter
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…
hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices
Farah Fahim, Benjamin Hawks, Christian Herwig +27
Accessible machine learning algorithms, software, and diagnostic tools for energy-efficient devices and systems are extremely valuable across a broad range of application domains.…
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference
Benjamin Hawks, Javier Duarte, Nicholas J. Fraser +3
Efficient machine learning implementations optimized for inference in hardware have wide-ranging benefits, depending on the application, from lower inference latency to higher data…