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Aug 23, 2019 · In this paper, we analyze a heterogeneous system composed of both of a tablet (client) and notebook with a low-power GPU (server).
Our system achieves better computational performance, and higher performance per watt than a tablet powered by a CUDA‐capable GPU. We achieved 21.7 Gflops/W by ...
CUDA offloading for energy‐efficient and high‐frame‐rate simulations using tablets. EJ Martinez‐Noriega, S Yazaki, T Narumi. Concurrency and Computation ...
Apr 25, 2024 · CUDA offloading for energy-efficient and high-frame-rate simulations using tablets. Concurr. Comput. Pract. Exp. 33(2) (2021); 2020. [c2]. view.
CUDA Offloading for Energy-Efficient and High-Frame-Rate Simulations using Tablets ; 巻 ; 号: e5488 ; 開始ページ: 1 ; 終了ページ: 14 ; 記述言語: 英語 ...
本論文では, GPU を使ったリアルタイムのシミュレーションを可視化する際に, 計算部. 分をネットワークの先にオフロードすることで計算効率を向上できることを示して ...
Jul 5, 2020 · The efficiency of GPU can be improved by decreasing the frequency of updating a frame to render. Nevertheless, this is not the optimal way to ...
Missing: energy- | Show results with:energy-
Aug 26, 2024 · New libraries in accelerated computing deliver order-of-magnitude speedups and reduce energy consumption and costs in data processing, generative AI, ...
Missing: offloading tablets.
In this work we present a performance comparison among the only three CUDA remote GPU virtualization frameworks publicly available at no cost. Results show that ...
May 26, 2023 · Programming on graphics cards using CUDA can become inefficient due to serial execution and programming overheads. The rest of this paper will ...