“AHA: An Agile Approach to the Design of Course-Grained Reconfigurable Accelerators and Compilers” by Kalhan Koul, Jackson Melchert, Kavya Sreedhar, Leonard Truong, Gedeon Nyengele, Keyi Zhang, Qiaoyi Liu, Jeff Setter, Po-Han Chen, Yuchen Mei, Maxwell Strange, Ross Daly, Caleb Donovick, Alex Carsello, Taeyoung Kong, Kathleen Feng, Dillon Huff, Ankita Nayak, Rajsekhar Setaluri, James Thomas, Nikhil Bhagdikar, David Durst, Zachary Myers, Nestan Tsiskaridze, Stephen Richardson, Rick Bahr, Kayvon Fatahalian, Pat Hanrahan, Clark Barrett, Mark Horowitz, Christopher Torng, Fredrik Kjolstad, and Priyanka Raina. ACM Transactions on Embedded Computing Systems, Apr. 2022.
With the slowing of Moore's law, computer architects have turned to domain-specific hardware specialization to continue improving the performance and efficiency of computing systems. However, specialization typically entails significant modifications to the software stack to properly leverage the updated hardware. The lack of a structured approach for updating both the compiler and the accelerator in tandem has impeded many attempts to systematize this procedure. We propose a new approach to enable flexible and evolvable domain-specific hardware specialization based on coarse-grained reconfigurable arrays (CGRAs). Our agile methodology employs a combination of new programming languages and formal methods to automatically generate the accelerator hardware and its compiler from a single source of truth. This enables the creation of design-space exploration frameworks that automatically generate accelerator architectures that approach the efficiencies of hand-designed accelerators, with a significantly lower design effort for both hardware and compiler generation. Our current system accelerates dense linear algebra applications, but is modular and can be extended to support other domains. Our methodology has the potential to significantly improve the productivity of hardware-software engineering teams and enable quicker customization and deployment of complex accelerator-rich computing systems.
BibTeX entry:
@article{KMS+22,
author = {Kalhan Koul and Jackson Melchert and Kavya Sreedhar and
Leonard Truong and Gedeon Nyengele and Keyi Zhang and Qiaoyi Liu
and Jeff Setter and Po-Han Chen and Yuchen Mei and Maxwell Strange
and Ross Daly and Caleb Donovick and Alex Carsello and Taeyoung
Kong and Kathleen Feng and Dillon Huff and Ankita Nayak and
Rajsekhar Setaluri and James Thomas and Nikhil Bhagdikar and David
Durst and Zachary Myers and Nestan Tsiskaridze and Stephen
Richardson and Rick Bahr and Kayvon Fatahalian and Pat Hanrahan
and Clark Barrett and Mark Horowitz and Christopher Torng and
Fredrik Kjolstad and Priyanka Raina},
title = {{AHA}: An Agile Approach to the Design of Course-Grained
Reconfigurable Accelerators and Compilers},
journal = {ACM Transactions on Embedded Computing Systems},
month = apr,
year = {2022},
doi = {10.1145/3534933},
url = {http://theory.stanford.edu/~barrett/pubs/KMS+22.pdf}
}
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