Research Collaboration and Enablement

The flexibility permitted by the Arm Scalable Vector Extension is valuable to computer architects looking to address the increasing computation requirements of HPC, data analytics and machine learning…

TinyML seeks to deploy ML algorithms on ultra low power systems, to enable us to intelligently select which data to transmit, improving energy efficiency.

Improving the characteristics of interconnects as device dimensions scale smaller.

Project Trishul demonstrates the feasibility and readiness of high-density, face-to-face, wafer-bonded 3D stacking technologies for high performance, energy-efficient designs.

University Program materials are now even easier to access via GitHub. Use our resources, tools and more to spark the potential of your students.

Connective and machine learning technologies offer previously unimagined solutions to solve complex real-world challenges that impact real lives. Haiyan Zhang, Director of Innovation at Microsoft Research…

The Arm Research Summit has been engaging academics, industry experts and researchers since 2016, promoting collaboration in a research led environment. Overtime the Summit has grown and developed, seeing…

Fixed functional hardware accelerators have been researched for many years, and it is well understood that they improve the performance and energy efficiency of a system. Integrating hardware accelerators…

Mango is an open source Python library for hyperparameter optimization, built for AutoML systems. Developed by Arm Research, Mango presents many useful features.

Concurrent programming is about the useful interaction of multiple processes over shared resources, and ensuring atomicity is just one of the challenges faced. The fundamental difficulty is that concurrent…

Researchers have studied neural network compression for quite some time. However, the need for always on compute has led to a recent trend towards executing these applications on even smaller IoT devices…

For present-day microprocessors, it is even more challenging to identify bugs. Using (ML) to efficiently identify bugs, we've seen a 25% increase in efficiency than the default verification workflow. …

When Dr. Timothy Jones finished his PhD and was looking to establish his career, one email to Arm changed everything. It led to new collaborators, invaluable industry insight and a high-level mentor.

2019 was yet another year of incredible technology discovery for Arm Research. Inspiring advancements have been made across the research community, and Arm Research has contributed to this. Our teams have…

In this blog series, we take a look back at some of the highlights from last year's Arm Research Summit. Interested in attending this year? Find out more here. Alasdair Russell from Cancer Research…

Arm has prioritised security, introducing TrustZone. A key component of TrustZone is the Secure Monitor, providing context switching between REE and TEE.

Emerging non-volatile memories (NVM), such as 3D XP and STT-MRAM, offer the promises of combining the performance and byte-addressability of DRAM with the density and non-volatility of NAND. Such non-volatile…

When the University of Michigan partnered with Arm Research on a project for DARPA, there was a remaining technical gap the team needed to bridge, and Arm Research knew the ideal partner.

Part two of the SMARTER blog series, decentralizing applications from data centers to machines closer to where valuable data is collected has become an catalyst for rethinking the way we manage application…

Presenting his SkyTalk at DAC 2020, Greg Yeric discusses his predictions for design and manufacturing in 2030.

Dr Nathan Chong (Principal Researcher, Arm) discusses his work with Tyler Sorensen (PhD student, Imperial College London) and Dr John Wickerson (Research Fellow, Imperial College London) on the semantics…