Rich OS Capabilities in High-Performance Compute Subsystems
With global infrastructure increasingly running on high-performance Arm Neoverse CPUs, academics can teach and research complex machine learning (ML) workloads, scaled multi-core cloud-native applications, and high performance computing (HPC). Arm Kleidi Libraries offer a lightweight suite of highly performant open-source routines to enable ML and computer vision (CV) frameworks to seamlessly leverage architectural features in Arm processors. This allows academic researchers interested in generative AI (GenAI), both on device and in the cloud, to take advantage of these advancements.
Featured Resources
RESOURCES | ML Examples
AI Applications on Neoverse with the Pytorch Framework Example
Get instructions and scripts to obtain and build Docker images containing PyTorch for ML applications, such as transformer-based natural language processing (NLP) and object detection, that can run on Arm CPU.
RESOURCES | Learning Paths
Find Arm-Based Cloud Service Providers with Academic Offers
Creating an account with a cloud service provider (CSPs) is the easiest way to get started with Arm-based infrastructure. CSPs offer introductory free credits to help you begin learning, and pay-as-you-go models make it easy to continue exploring Arm hardware at minimal cost. This directory lists existing offers that academics can take advantage of.
DEVELOPER | Arm Developer
On-Device AI and ML
Get educational materials, ranging for beginner to advanced, on how to run your GenAI and ML workloads locally on Android devices.
Developer Resources
DEVELOPER | Arm Developer
Get Institution-Wide Access to Arm Development Studio
Access a dedicated IDE, including the Arm Compiler for embedded and optimized libraries across Cortex-A applications. Universities can access a free institution-wide license.
DEVELOPER | Arm Developer
View a Curated List of Software Libraries Natively Available for Arm
Access an index of third-party software natively built for Arm. This resource is valuable when architecting new software to run on Arm and managing dependencies during software porting.
RESOURCES | Learning Paths
Deploy a LLM on an Arm Neoverse Instructions
Learn how to deploy llama.cpp on an Arm based server and re-quantize the model weights to take advantage of optimizations.
Other Resources
RESOURCES | Arm Developer
Access Resources for Developing on Windows on Arm
Access resources from Arm and Microsoft for porting and optimizing applications to natively run on Windows for Arm.
RESOURCES | Learning Paths
Servers and Cloud Computing Guides
Get step-by-step guides to help academics develop software on Arm-based servers and cloud infrastructure.
RESOURCES | Learning Paths
Laptops and Desktops Guides
Get step-by-step guides to help academics develop software on Arm-based laptops and desktops.
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