Wave Computing Joins Industry and Academic Leaders to Define Next-Generation Machine Learning Industry Benchmark

THE O’REILLY AI CONFERENCE, N.Y., May 02, 2018 -- Wave Computing^®, the Silicon Valley company that is revolutionizing artificial intelligence (AI) and deep learning with its dataflow-based systems, announced today it is joining forces with innovators from Baidu, Google, Harvard University, Stanford University, University of California, Berkeley, and more, to help define a new machine learning benchmark for data scientists. The MLPerf benchmark will enable more accurate evaluation of the performance and scalability of neural network workloads, as well as the ability of compute systems to train and inference production-sized datasets. MLPerf aims to set a new standard for the AI industry by using real life scenarios, unlike many benchmarks used today which are typically based on outdated methodologies or biased to traditional hardware architectures. When finalized, MLPerf will be openly available in the public domain for general use and evolution.

As the demand for AI grows, data scientists need a more reliable way to anticipate how their models and acceleration platforms will behave while performing tasks spanning natural language understanding to image recognition. The difference of seconds between predicted and actual results can mean millions of dollars in lost revenue opportunities for companies using AI in industries spanning retail, financial services and public cloud. By drawing on lessons from the 40-year history of computer benchmarking and leveraging some of the brightest minds in academia and industry, MLPerf will “close the gap” while enabling a fair comparison of competing algorithms and systems, and improving innovation in AI.

“Wave Computing is honored to have been invited by the organizers of the MLPerf benchmark consortium to participate in this exciting and much-needed effort,” said Dr. Chris Nicol, CTO of Wave Computing. “The AI industry clearly needs a better benchmark solution to keep pace with the quickly evolving nature of neural networks. We look forward to contributing to this important collaboration between industry professionals and academic researchers.”

About the MLPerf Benchmark
MLPerf will be a new benchmark for measuring the speed of machine learning software and hardware based on the time it takes to train deep neural networks to perform tasks including recognizing objects and translating languages. MLPerf will evaluate metrics such as quality, accuracy, execution time, power, and cost to run the suite. The effort is support by a broad coalition of organizations including Baidu, Google, Harvard University, Intel, Microsoft, Sambanova, Stanford University, University of California, Berkeley, University of Minnesota, University of Toronto, and Wave Computing.

About Wave Computing
Wave Computing, Inc. is the Silicon Valley company that is revolutionizing artificial intelligence and deep learning with its dataflow-based systems. The company’s vision is to “follow the data” and bring deep learning to customers’ data wherever it may be—from the datacenter to the edge of the cloud. Offering its solutions to customers globally, Wave Computing has been named Frost & Sullivan’s 2018 “Machine Learning Industry Technology Innovation Leader,” and has been recognized by CIO Application Magazine’s as one of the “Top 25 Artificial Intelligence Providers.”

Wave Computing and the Wave Computing logo are trademarks of Wave Computing, Inc. All other trademarks are used for identification purposes only and are the property of their respective owners. ©2018 Wave Computing, Inc.  All rights reserved.

Media Contact:
Fadi Azhari     
Vice President, Marketing                
Wave Computing                                            
+1 650.575.7119
[email protected]