AI Bibliography
AI Bibliography |
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Hill, M., & Reddi, V. J. 2019, Gables: A roofline model for mobile socs. Paper presented at 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA). |
| Resource type: Proceedings Article BibTeX citation key: Hill2019 View all bibliographic details  |
Categories: Artificial Intelligence, Computer Science, Data Sciences, Engineering, General, Innovation Subcategories: Big data, Edge AI Creators: Hill, Reddi Publisher: Collection: 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA) |
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Over a billion mobile consumer system-on-chip (SoC) chipsets ship each year. Of these, the mobile consumer market undoubtedly involving smartphones has a significant market share. Most modern smartphones comprise of advanced SoC architectures that are made up of multiple cores, GPS, and many different programmable and fixed-function accelerators connected via a complex hierarchy of interconnects with the goal of running a dozen or more critical software usecases under strict power, thermal and energy constraints. The steadily growing complexity of a modern SoC challenges hardware computer architects on how best to do early stage ideation. Late SoC design typically relies on detailed full-system simulation once the hardware is specified and accelerator software is written or ported. However, early-stage SoC design must often select accelerators before a single line of software is written. To help frame SoC thinking and guide early stage mobile SoC design, in this paper we contribute the Gables model that refines and retargets the Roofline model---designed originally for the performance and bandwidth limits of a multicore chip---to model each accelerator on a SoC, to apportion work concurrently among different accelerators (justified by our usecase analysis), and calculate a SoC performance upper bound. We evaluate the Gables model with an existing SoC and develop several extensions that allow Gables to inform early stage mobile SoC design.
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