Hyperlight Nanvix: POSIX support for Hyperlight Micro-VMs
The Cloud Native Computing Foundation’s (CNCF) Hyperlight project delivers faster, more secure, and smaller workload execution to the cloud-native ecosystem.
The Cloud Native Computing Foundation’s (CNCF) Hyperlight project delivers faster, more secure, and smaller workload execution to the cloud-native ecosystem.
ONNX models can be accelerated with ONNX Runtime, which works cross-platform and provides coverage for many cloud and language models.
ONNX Runtime harnesses Intel® AMX to accelerate performance for the 4th Gen Intel® Xeon® CPUs.
KEDA reduces the complexity of infrastructure autoscaling, making it simpler to configure, manage, and secure the application auto-scaler.
ONNX Script is a new open-source library for directly authoring ONNX models in Python.
Using ONNX Runtime to unlock the promise of developments in science for solving real world problems.
Building upon the foundation we established earlier, this blog will present comprehensive information about the underlying details of training models directly on user devices using ORT. Equipped with these technical details, we encourage you to try out On-Device Training with ONNX Runtime for your custom scenario.
Introducing Olive, an easy-to-use toolchain for optimizing models with hardware awareness. With Olive, you don't need to be an expert to explore diverse hardware optimization toolchains.
Intel has collaborated with Microsoft to integrate Intel® Neural Compressor into Olive, enabling developers to easily take advantage of model compression techniques in their deployment platform, including Intel processors and accelerators.
ONNX Runtime is a high-performance cross-platform inference and training engine that can run a variety of machine learning models. ORT provides an easy-to-use experience for the AI developers to run models on multiple hardware and software platforms.
As the requirements and software surrounding Kubernetes clusters grow along with the required number of clusters, the administrative overhead becomes overwhelming and unsustainable without an appropriate architecture and supportive tooling.
As we come together in Amsterdam, there are significant headwinds and challenges facing us, but I’m confident that open-source and cloud-native computing are critical parts of the solutions.
In this blog post, we’ll share challenges our team faced, and how ONNX Runtime solves these as the backbone of success for high-performance inferencing.
Azure Open Source Day highlighted Microsoft’s commitment to open Source and focused on how Open Source Technologies can be used to build intelligent apps faster and with more flexibility.