222 citations · 768 across the 21 of their papers we have counts for
22 papers
Hardware Abstractions and Hardware Mechanisms to Support Multi-Task Execution on Coarse-Grained Reconfigurable Arrays
Taeyoung Kong, Kalhan Koul, Priyanka Raina +2
Domain-specific accelerators are used in various computing systems ranging from edge devices to data centers. Coarse-grained reconfigurable arrays (CGRAs) represent an architectura…
Vision Transformer Computation and Resilience for Dynamic Inference
Kavya Sreedhar, Jason Clemons, Rangharajan Venkatesan +2
State-of-the-art deep learning models for computer vision tasks are based on the transformer architecture and often deployed in real-time applications. In this scenario, the resour…
Canal: A Flexible Interconnect Generator for Coarse-Grained Reconfigurable Arrays
Jackson Melchert, Keyi Zhang, Yuchen Mei +3
The architecture of a coarse-grained reconfigurable array (CGRA) interconnect has a significant effect on not only the flexibility of the resulting accelerator, but also its power,…
Cascade: An Application Pipelining Toolkit for Coarse-Grained Reconfigurable Arrays
Jackson Melchert, Yuchen Mei, Kalhan Koul +3
While coarse-grained reconfigurable arrays (CGRAs) have emerged as promising programmable accelerator architectures, pipelining applications running on CGRAs is required to ensure…
The Sparse Abstract Machine
Olivia Hsu, Maxwell Strange, Ritvik Sharma +5
We propose the Sparse Abstract Machine (SAM), an abstract machine model for targeting sparse tensor algebra to reconfigurable and fixed-function spatial dataflow accelerators. SAM…
Bringing Source-Level Debugging Frameworks to Hardware Generators
Keyi Zhang, Zain Asgar, Mark Horowitz
High-level hardware generators have significantly increased the productivity of design engineers. They use software engineering constructs to reduce the repetition required to expr…