3 papers
cs.AR2026
Design and Evaluation of Energy-Efficient Whisper Dot-Product Kernel Offloading on a CGLA Architecture
Takuto Ando, Yu Eto, Ayumu Takeuchi +1
In this paper, we implement and evaluate Whisper dot-product kernel offloading on IMAX, a programmable Coarse-Grained Linear Arrays (CGLAs) architecture. Whisper-tiny.en profiling…
cs.AR2025
Efficient Kernel Mapping and Comprehensive System Evaluation of LLM Acceleration on a CGLA
Takuto Ando, Yu Eto, Ayumu Takeuchi +1
Large Language Models (LLMs) demand substantial computational resources, resulting in high energy consumption on GPUs. To address this challenge, we focus on Coarse-Grained Reconfi…
cs.AR2025
Energy-Efficient Hardware Acceleration of Whisper ASR on a CGLA
Takuto Ando, Yu Eto, Ayumu Takeuchi +1
The rise of generative AI for tasks like Automatic Speech Recognition (ASR) has created a critical energy consumption challenge. While ASICs offer high efficiency, they lack the pr…