5 citations · 5 across the 1 of their papers we have counts for
2 papers
cs.AR2020
Enabling High-Capacity, Latency-Tolerant, and Highly-Concurrent GPU Register Files via Software/Hardware Cooperation
Mohammad Sadrosadati, Amirhossein Mirhosseini, Ali Hajiabadi +7
Graphics Processing Units (GPUs) employ large register files to accommodate all active threads and accelerate context switching. Unfortunately, register files are a scalability bot…
cs.LG2019★ 5 cited
ORIGAMI: A Heterogeneous Split Architecture for In-Memory Acceleration of Learning
Hajar Falahati, Pejman Lotfi-Kamran, Mohammad Sadrosadati +1
Memory bandwidth bottleneck is a major challenges in processing machine learning (ML) algorithms. In-memory acceleration has potential to address this problem; however, it needs to…