Implementation and Evaluation of Stable Diffusion on a General-Purpose CGLA Accelerator
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908628086161408 |
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| author | Ando, Takuto Eto, Yu Nakashima, Yasuhiko |
| author_facet | Ando, Takuto Eto, Yu Nakashima, Yasuhiko |
| contents | This paper presents the first implementation and in-depth evaluation of the primary computational kernels from the stable-diffusion.cpp image generation framework on IMAX3, a general-purpose Coarse-Grained Reconfigurable Array (CGRA) accelerator. We designed IMAX3 as a versatile computational platform, and this work assesses its capabilities by executing a demanding image generation workload. We evaluate its performance on a current Field-Programmable Gate Array (FPGA) prototype to establish a baseline and project its potential for a future Application-Specific Integrated Circuit (ASIC) implementation. Our results demonstrate that, despite its general-purpose architecture, IMAX3 achieves promising performance and power efficiency, particularly in its projected ASIC form. This work provides concrete guidelines for future IMAX architectural designs and establishes a foundation for developing next-generation, AI-specialized Coarse-Grained Linear Array (CGLA) accelerators by refining this versatile platform. Ultimately, this achievement contributes to the realization of energy-efficient, on-device, multi-modal AI platforms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_02530 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Implementation and Evaluation of Stable Diffusion on a General-Purpose CGLA Accelerator Ando, Takuto Eto, Yu Nakashima, Yasuhiko Hardware Architecture This paper presents the first implementation and in-depth evaluation of the primary computational kernels from the stable-diffusion.cpp image generation framework on IMAX3, a general-purpose Coarse-Grained Reconfigurable Array (CGRA) accelerator. We designed IMAX3 as a versatile computational platform, and this work assesses its capabilities by executing a demanding image generation workload. We evaluate its performance on a current Field-Programmable Gate Array (FPGA) prototype to establish a baseline and project its potential for a future Application-Specific Integrated Circuit (ASIC) implementation. Our results demonstrate that, despite its general-purpose architecture, IMAX3 achieves promising performance and power efficiency, particularly in its projected ASIC form. This work provides concrete guidelines for future IMAX architectural designs and establishes a foundation for developing next-generation, AI-specialized Coarse-Grained Linear Array (CGLA) accelerators by refining this versatile platform. Ultimately, this achievement contributes to the realization of energy-efficient, on-device, multi-modal AI platforms. |
| title | Implementation and Evaluation of Stable Diffusion on a General-Purpose CGLA Accelerator |
| topic | Hardware Architecture |
| url | https://arxiv.org/abs/2511.02530 |