2 papers
cs.LG2025
BLaST: High Performance Inference and Pretraining using BLock Sparse Transformers
Patrik Okanovic, Sameer Deshmukh, Grzegorz Kwasniewski +8
The energy consumption of large-scale ML models is dominated by data movement, shuffling billions of parameters across memory hierarchies and data centers. Sparsification offers a…
cs.AR2024
Evaluation of Posits for Spectral Analysis Using a Software-Defined Dataflow Architecture
Sameer Deshmukh, Daniel Khankin, William Killian +2
Spectral analysis plays an important role in detection of damage in structures and deep learning. The choice of a floating-point format plays a crucial role in determining the accu…