5 citations · 7 across the 3 of their papers we have counts for
3 papers
Morpheus: Extending the Last Level Cache Capacity in GPU Systems Using Idle GPU Core Resources
Sina Darabi, Mohammad Sadrosadati, Joël Lindegger +6
Graphics Processing Units (GPUs) are widely-used accelerators for data-parallel applications. In many GPU applications, GPU memory bandwidth bottlenecks performance, causing underu…
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…
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…