by Angela Guess
According to a recent press release, “Baidu Research, a division of Baidu Inc., today unveiled the next generation of DeepBench, the open source deep learning benchmark that now includes measurement for inference. The announcement was made at the O’Reilly AI Conference in New York. In September of 2016, Baidu released the initial version of DeepBench, which became the first tool to be opened up to the wider deep learning community to evaluate how different processors perform when they are used to train deep neural networks. Since its initial release, several companies have used and contributed to the DeepBench platform, including Intel, Nvidia, and AMD.”
The release continues, “Following positive feedback from peers across the AI industry and academia, Baidu Research has now incorporated requests to include the measurement of deep learning inference, in addition to training, across different hardware platforms. Inference involves using a previously trained model to make predictions on a new data set. ‘Measuring inference is critical,’ said Dr. Greg Diamos, Senior Researcher at Baidu Research Silicon Valley AI Lab. ‘It covers the operations needed to run neural networks on a device, be it in the cloud, on a phone or a wearable. A better understanding of performance of inference means better chips and neural networks in real products.’ Benchmarking inference is a challenging problem. Many applications that have been enabled by deep learning each have their own unique performance characteristics and requirements. In addition, there are several different deployment platforms. DeepBench attempts to solve this problem by benchmarking fundamental operations required for inference.”
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Photo credit: Baidu