{"id":28941,"date":"2022-04-06T11:08:12","date_gmt":"2022-04-06T18:08:12","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=28941"},"modified":"2022-04-06T11:08:15","modified_gmt":"2022-04-06T18:08:15","slug":"deci-boosts-computer-vision-nlp-models-performance-at-mlperf","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2022\/04\/06\/deci-boosts-computer-vision-nlp-models-performance-at-mlperf\/","title":{"rendered":"Deci Boosts Computer Vision & NLP Models\u2019 Performance at MLPerf\u00a0"},"content":{"rendered":"\n
\"\"<\/figure><\/div>\n\n\n\n

Deci<\/a>, the deep learning company harnessing Artificial Intelligence (AI) to build AI, announced its results for both Computer Vision (CV) and Natural Language Processing (NLP) inference models that were submitted to the MLPerf v2.0\u00a0Datacenter Open division. These submissions demonstrated the power of Deci\u2019s Automated Neural Architecture Construction (AutoNAC) technology, which automatically generated models dubbed DeciNets and DeciBERT, thus delivering breakthrough accuracy and throughput performance on Intel\u2019s CPUs.<\/p>\n\n\n\n

\u201cWe are excited to showcase another significant milestone in our journey to enable efficient deep learning inference on any hardware including resource constrained devices such as CPUs\u00a0and other edge devices\u201d said Yonatan Geifman, CEO and co-founder of Deci. \u201cThis major increase both in accuracy and throughput means that resource-intensive tasks that previously could not be carried out on CPUs are now possible, and in fact, will see a marked performance improvement. Hardware availability or compute power should never be a limiting factor for enterprises looking to employ the latest developments in deep learning.\u201d<\/p><\/blockquote>\n\n\n\n

For their CV submission, Deci submitted three of its DeciNets models in the ResNet50 category under the offline scenario in the open division. Deci made submissions on two different hardware platforms: a 12-core Intel Cascade Lake CPU and two different Intel Ice Lake CPUs with 4 and 32-cores. Models were optimized on a batch size of 32 and quantized to INT8 using OpenVINO. Compared to the 8-bit ResNet50 model, Deci delivered +1.74% improvement in accuracy and 4x improvement in throughput.<\/p>\n\n\n\n

Deci\u2019s CV submission this year demonstrated a 37% improvement<\/em> in throughput performance, as well as a notable improvement in accuracy, compared to their previous submission in 2020.<\/a><\/p>\n\n\n\n

For NLP, Deci submitted its optimized DeciBERT models that produced outstanding results: accelerating question-answering tasks\u2019 throughput performance on various Intel CPUs by 5x (depending on the hardware type and quantization level) while also improving the accuracy by +1.03%. <\/p>\n\n\n\n

MLPerf<\/a> gathers expert deep learning leaders to build fair and useful benchmarks for measuring training and inference performance of ML hardware, software, and services. The models submitted were optimized using Deci\u2019s AutoNAC technology and quantized with Intel\u2019s OpenVINO to 8-bit precision. <\/p>\n\n\n\n

Deci\u2019s AI-based AutoNAC technology automatically generates and optimizes deep learning architecture for any given data set and hardware to maximize its accuracy and inference performance. Deci\u2019s AutoNAC technology, as well as its auto-generated DeciNets & DeciBERT, are ready for deployment and commercial use and can be easily integrated to support any CV or NLP task on a wide range of hardware types.<\/p>\n\n\n\n

Deci\u2019s Computer Vision Submission Results:<\/strong><\/p>\n\n\n\n

Computer Vision Submission:<\/strong><\/p>\n\n\n\n

Accuracy and Throughput [samples\/sec] Results on Different Hardware Types<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Deci\u2019s NLP Submission Results: <\/strong><\/p>\n\n\n\n

Accuracy and Throughput [samples\/sec] Results on Different Hardware Types<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Sign up for the free insideBIGDATA newsletter<\/a>.<\/em><\/p>\n\n\n\n

Join us on Twitter: @InsideBigData1 \u2013 https:\/\/twitter.com\/InsideBigData1<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Deci, the deep learning company harnessing Artificial Intelligence (AI) to build AI, announced its results for both Computer Vision (CV) and Natural Language Processing (NLP) inference models that were submitted to the MLPerf v2.0\u00a0Datacenter Open division. These submissions demonstrated the power of Deci\u2019s Automated Neural Architecture Construction (AutoNAC) technology, which automatically generated models dubbed DeciNets and DeciBERT, thus delivering breakthrough accuracy and throughput performance on Intel\u2019s CPUs.<\/p>\n","protected":false},"author":10513,"featured_media":28944,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[526,115,182,180,67,56,84,1],"tags":[437,324,581,941,635,96],"acf":[],"yoast_head":"\nDeci Boosts Computer Vision & NLP Models\u2019 Performance at MLPerf\u00a0 - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2022\/04\/06\/deci-boosts-computer-vision-nlp-models-performance-at-mlperf\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Deci Boosts Computer Vision & NLP Models\u2019 Performance at MLPerf\u00a0 - insideBIGDATA\" \/>\n<meta property=\"og:description\" content=\"Deci, the deep learning company harnessing Artificial Intelligence (AI) to build AI, announced its results for both Computer Vision (CV) and Natural Language Processing (NLP) inference models that were submitted to the MLPerf v2.0\u00a0Datacenter Open division. 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