Fpga は、次世代の 深い学習 を加速する上で Gpu を打つことができるか。|Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Learning?

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• Fpga は、次世代の 深い学習 を加速する上で Gpu を打つことができるか。|Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Learning?

日本語

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English

Continued exponential growth of digital data of images, videos, and speech from sources such as social media and the internet-of-things is driving the need for analytics to make that data understandable and actionable. Data analytics often rely on machine learning (ML) algorithms. Among ML algorithms, deep convolutional neural networks (DNNs) offer state-of-the-art accuracies for important image classification tasks and are becoming widely adopted. At the recent International Symposium on Field Programmable Gate Arrays (ISFPGA), Dr. Eriko Nurvitadhi from Intel Accelerator Architecture Lab (AAL), presented research on Can FPGAs beat GPUs in Accelerating Next-Generation Deep Neural Networks.
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