Treffer: Enhancing High-Level Synthesis Using a Meta-Programming Approach.
Weitere Informationen
In today's increasingly heterogeneous compute landscape, there is high demand for design tools that offer seemingly contradictory features: portable programming abstractions that hide underlying architectural detail, and the capability to optimise and exploit architectural features. Our meta-programming approach, Artisan, decouples application functionality from optimisation concerns to address the complexity of mapping high-level application descriptions onto heterogeneous platforms from which they are abstracted. With Artisan, application experts focus on algorithmic behaviour, while platform and domain experts focus on optimisation and mapping. Artisan offers complete design-flow orchestration in a unified programming environment based on Python 3 to enable accessible codification of reusable optimisation strategies that can be automatically applied to high-level application descriptions. We have developed and evaluated an Artisan prototype and a set of customised meta-programs used to automatically optimise six case study applications for CPU+FPGA targets. In our experiments, Artisan-optimised designs achieve the same order of magnitude speedup as manually optimised designs compared to corresponding unoptimised software. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Computers is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)