دانلود مقاله انگلیسی رایگان:معیار عملکرد و بهره وری انرژی شتاب دهنده های هوش مصنوعی برای آموزش هوش مصنوعی - 2020
بلافاصله پس از پرداخت دانلود کنید
دانلود مقاله انگلیسی هوش مصنوعی رایگان
  • Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training
    Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Benchmarking the Performance and Energy Efficiency of AI Accelerators for AI Training


    ترجمه فارسی عنوان مقاله:

    معیار عملکرد و بهره وری انرژی شتاب دهنده های هوش مصنوعی برای آموزش هوش مصنوعی


    منبع:

    IEEE - 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID);2020; ; ;10.1109/CCGrid49817.2020.00-15


    نویسنده:

    Yuxin Wang, Qiang Wang, Shaohuai Shi, Xin He, Zhenheng Tang, Kaiyong Zhao, Xiaowen Chu


    چکیده انگلیسی:

    Deep learning has become widely used in complex AI applications. Yet, training a deep neural network (DNNs) model requires a considerable amount of calculations, long running time, and much energy. Nowadays, many-core AI accelerators (e.g., GPUs and TPUs) are designed to improve the performance of AI training. However, processors from different vendors perform dissimilarly in terms of performance and energy consumption. To investigate the differences among several popular off-theshelf processors (i.e., Intel CPU, NVIDIA GPU, AMD GPU, and Google TPU) in training DNNs, we carry out a comprehensive empirical study on the performance and energy efficiency of these processors 1 by benchmarking a representative set of deep learning workloads, including computation-intensive operations, classical convolutional neural networks (CNNs), recurrent neural networks (LSTM), Deep Speech 2, and Transformer. Different from the existing end-to-end benchmarks which only present the training time, We try to investigate the impact of hardware, vendor’s software library, and deep learning framework on the performance and energy consumption of AI training. Our evaluation methods and results not only provide an informative guide for end users to select proper AI accelerators, but also expose some opportunities for the hardware vendors to improve their software library.
    Index Terms: AI Accelerator | Deep Learning | CPU | GPU | TPU | Computation-intensive Operations | Convolution Neural Networks | Recurrent Neural Networks | Transformer | Deep Speech 2


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 8
    حجم فایل: 823 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




اگر این مقاله را پسندیدید آن را در شبکه های اجتماعی به اشتراک بگذارید (برای به اشتراک گذاری بر روی ایکن های زیر کلیک کنید)

تعداد نظرات : 0

الزامی
الزامی
الزامی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi