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Introducing ONNX Runtime mobile – a reduced size, high performance package for edge devices 

ONNX Runtime is an open source project that is designed to accelerate machine learning across a wide range of frameworks, operating systems, and hardware platforms. Today, we are excited to announce ONNX Runtime release v1.5 as part of our AI at Scale initiative. This release includes ONNX Runtime mobile, a new feature targeting smartphones and other...Read more

Accelerate traditional machine learning models on GPU with ONNX Runtime 

With the growing trend towards deep learning techniques in AI, there are many investments in accelerating neural network models using GPUs and other specialized hardware. However, many models used in production are still based on traditional machine learning libraries or sometimes a combination of traditional machine learning (ML) and DNNs. We’ve previously shared the performance...Read more

Open-sourcing TensorFlow with DirectML 

Following the release of our Developer Preview in June, today we’re announcing an exciting next step as we make the source code of TensorFlow-DirectML, an extension of TensorFlow on Windows, available to the public as an open-source project on GitHub. TensorFlow-DirectML broadens the reach of TensorFlow beyond its traditional Graphics Processing Unit (GPU) support, by...Read more

GPT-2 fine-tuning with ONNX Runtime – a 34% speedup in training time 

Model training is an important step when developing and deploying large scale Artificial Intelligence (AI) models. Training typically utilizes a large amount of compute resources to tune the model based on the input dataset. Transformer models, with millions and billions of parameters, are especially compute-intensive and training costs increase with model size and fine-tuning steps...Read more

Hyperspace, an indexing subsystem for Apache Spark™, is now open source 

For Microsoft’s internal teams and external customers, we store datasets that span from a few GBs to 100s of PBs in our data lake. The scope of analytics on these datasets ranges from traditional batch-style queries (e.g., OLAP) to explorative ”finding the needle in a haystack” type of queries (e.g., point-lookups, summarization). Resorting to linear...Read more

Announcing accelerated training with ONNX Runtime—train models up to 45% faster 

ONNX Runtime is an open source project that is designed to accelerate machine learning across a wide range of frameworks, operating systems, and hardware platforms. It is used extensively in Microsoft products, like Office 365 and Bing, delivering over 20 billion inferences every day and up to 17 times faster inferencing. Today we are introducing...Read more

Microsoft open sources breakthrough optimizations for transformer inference on GPU and CPU 

This post is co-authored by Emma Ning, Azure Machine Learning; Nathan Yan, Azure Machine Learning; Jeffrey Zhu, Bing; Jason Li, Bing One of the most popular deep learning models used for natural language processing is BERT (Bidirectional Encoder Representations from Transformers). Due to the significant computation required, inferencing BERT at high scale can be extremely...Read more

Announcing Applied Cloud Stories 

We are delighted to announce the Applied Cloud Stories initiative by Microsoft! What is Applied Cloud Stories? Do you work with open source? Are you passionate about machine learning or data science? Do you have stories to share about solving scale or data challenges? Are you investing time and effort so that you and your...Read more

ONNX joins Linux Foundation 

Today the Open Neural Network eXchange (ONNX) is joining the LF AI Foundation, an umbrella foundation of the Linux Foundation supporting open source innovation in artificial intelligence, machine learning, and deep learning. ONNX was co-founded by Microsoft in 2017 to make it easier to create and deploy machine learning applications. In the past few years,...Read more

Announcing ONNX Runtime 1.0 

One year after ONNX Runtime’s initial preview release, we’re excited to announce v1.0 of the high-performance machine learning model inferencing engine. This release marks our commitment to API stability for the cross-platform, multi-language APIs, and introduces a breadth of performance optimizations, broad operator coverage, and pluggable accelerators to take advantage of new and exciting hardware...Read more

Now available: ONNX Runtime 0.5 with support for edge hardware acceleration 

ONNX Runtime 0.5, the latest update to the open source high performance inference engine for ONNX models, is now available. This release improves the customer experience and supports inferencing optimizations across hardware platforms. Since the last release in May, Microsoft teams have deployed an additional 45+ models that leverage ONNX Runtime for inferencing. These models...Read more

Microsoft joins partners and the Linux Foundation to create Confidential Computing Consortium 

Microsoft has invested in confidential computing for many years, so I’m excited to announce that Microsoft will join industry partners to create the Confidential Computing Consortium, a new organization that will be hosted at The Linux Foundation. The Confidential Computing Consortium will be dedicated to defining and accelerating the adoption of confidential computing. Confidential computing...Read more