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Paper Abstract and Keywords
Presentation 2026-06-01 14:40
Future Directions and Implementation of an Integrated Software Stack for Diverse AI Workloads on CGLA
Takuto Ando, Yoshifumi Munakata, Yasuhiko Nakashima (NAIST) CPSY2026-1 DC2026-1 RECONF2026-1
Abstract (in Japanese) (See Japanese page) 
(in English) As AI workloads diversify, inference platforms must provide both power efficiency and the flexibility to support a range of workloads. GPUs are highly programmable but power-hungry, whereas dedicated ASICs are efficient but typically tailored to specific workloads. FPGAs are flexible, but their operating frequency and execution performance are often limited. In this paper, we present a common implementation approach and an initial evaluation for ggml-based OSS workloads on CGLA/IMAX, including llama.cpp, whisper.cpp, and stable-diffusion.cpp. In llama.cpp, we offload CPU-side matrix multiplication and dot-product kernels to IMAX and extend the same implementation boundary to ASR and image generation workloads. Our prior results show that LLM decode is dominated by LOAD and host-side processing, Q-Snap improves prefill performance by 1.62x, Whisper ASR achieves 1.90x and 9.83x higher energy efficiency than Jetson AGX Orin and RTX 4090, respectively, and Stable Diffusion is implemented with mixed FP16/FP32/quantized execution. Based on these observations, we discuss software-stack issues for CGLA, including a common frontend, a measurement-driven runtime, and policy-specialized backends.
Keyword (in Japanese) (See Japanese page) 
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Reference Info. IEICE Tech. Rep., vol. 126, no. 49, CPSY2026-1, pp. 1-6, June 2026.
Paper # CPSY2026-1 
Date of Issue 2026-05-25 (CPSY, DC, RECONF) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF CPSY2026-1 DC2026-1 RECONF2026-1

Conference Information
Committee CPSY DC RECONF IPSJ-ARC  
Conference Date 2026-06-01 - 2026-06-03 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To CPSY 
Conference Code 2026-06-CPSY-DC-RECONF-ARC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Future Directions and Implementation of an Integrated Software Stack for Diverse AI Workloads on CGLA 
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1st Author's Name Takuto Ando  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Yoshifumi Munakata  
2nd Author's Affiliation Nara Institute of Science and Technology (NAIST)
3rd Author's Name Yasuhiko Nakashima  
3rd Author's Affiliation Nara Institute of Science and Technology (NAIST)
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Speaker Author-1 
Date Time 2026-06-01 14:40:00 
Presentation Time 20 minutes 
Registration for CPSY 
Paper # CPSY2026-1, DC2026-1, RECONF2026-1 
Volume (vol) vol.126 
Number (no) no.49(CPSY), no.50(DC), no.51(RECONF) 
Page pp.1-6 
#Pages 6 
Date of Issue 2026-05-25 (CPSY, DC, RECONF) 

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