Discover how the PSA Crypto API allows developers to transparently access security functionality residing on and off the chip, along with other APIs which make it even easier to access security functionality…

In part-two we continue to explore the simulation, characterization, and analysis of MRAM stochasticity, sharing a compact model and framework.

In part-two of the scalable MTJ simulation, we share a compact model and framework for the efficient and scalable simulation of circuits with MRAMs.

PlasticArm is bringing the possibility of seamlessly embedding billions of extremely low-cost, ultra-thin, conformable microprocessors into everyday objects – a significant leap forward in realising the…

Buried interconnects can help mitigate the interconnect resistance issue and augment the technology scaling roadmap for sub-5nm process nodes.

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

We share the experiences of four of our colleagues, offering professional advice for those starting their career, and aiding understanding of what it's like to be a women in engineering.

Our research explores how adding new explicit instructions which define their fine-grain ordering requirements could reduce the need for memory barriers.

IoT devices collect and transmit data to the cloud, where it is then analyzed and ML models trained. Privacy challenges arise when users are reluctant to share their personal data.

The workshop held in conjunction with MLSys 2021 brought researchers and practitioners together to discuss key issues, share new research results and practical tutorial material.

Arm Research is excited to be part of the Cambridge ELLIS Unit, focusing on two key elements: Bayesian statistics and Probabilistic ML.

Our approach to creating a shared Edge computing framework borrows from the cloud, where a user allocates resources in each physical node it requests access to.

With the proliferation of smart devices, we need to make sure we are protecting our data. But have you ever considered the threat to the hardware supply chain?

Veracruz explores how novel, data-intensive distributed systems can be built using Strong Isolation Technologies and remote attestation.

Looking at how to make computers fundamentally more secure, the University of Cambridge with DARPA created CHERI, making compartmentalization more efficient and scalable.

Hardware-based coherence has simplified concurrent programming, and our work shows the improvements in performance and programmability.

It is important in industry to define what we see and how well we see it. This simple yet powerful idea has driven recent developments in the Arm Research ML Lab.

The Barcelona Supercomputing Center – Arm Research Centre of Excellence was formed to recognize the leadership and hard work in pioneering Arm in HPC.

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

A single label is not enough. Label diversity can be introduced by creating several labels for each training example in a way that the ordinal structure allows.

As part of DARPA’s Domain-Specific System on Chip program, Arizona State University assembled a team of academics and industry partners to pioneer a new approach to software-enabled radio frequency.