3 papers
cs.AR2026
AIA: A Customized Multi-core RISC-V SoC for Discrete Sampling Workloads in 16 nm
Shirui Zhao, Nimish Shah, Wannes Meert +1
Probabilistic models (PMs) are essential in advancing machine learning capabilities, particularly in safety-critical applications involving reasoning and decision-making. Among the…
eess.SY2026
SparseCol: A 1320 BTOPS/W Precision-scalable NPU Exploiting Training-free Structured Bit-level Sparsity and Dynamic Dataflow
Man Shi, Vikram Jain, Weijie Jiang +4
Bit-serial computation enables sequential processing of data at the bit level, providing several advantages, such as scalable computational precision. This approach has gained sign…
cs.AR2025
How to keep pushing ML accelerator performance? Know your rooflines!
Marian Verhelst, Luca Benini, Naveen Verma
The rapidly growing importance of Machine Learning (ML) applications, coupled with their ever-increasing model size and inference energy footprint, has created a strong need for sp…