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.
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.
In our first blog of National Inclusion Week, we discuss embracing and valuing differences. In Arm Research, we understand that diversity is key to creating and delivering innovative technology for the…
At the heart of computing at the edge, we find efficient low-power signal processors and ML accelerators. However, limits on compute and memory resources restrict the size and the complexity of the ML…
We are celebrating National Inclusion Week, and in part two of our three part series, we're exploring the career paths of some of our colleagues in Arm Research.
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 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.
Operational semantics are a precise, mathematical description of how a storage system should behave, and parametric in the choice of the consistency model.
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?
Registration is now open for the virtual Arm Research Summit 2020. This year we are discussing global technology challenges. Join us for free, September 9-11.
Most conventional FPGA-based accelerators use off-chip memory for data transformation, then perform computation for a single-layer in a time-multiplexed manner. Throughput is often limited by the memory…
Korea Electronics Technology Institute director Sungho Lee gives us the lowdown on their Radar SoC innovations – and how his team’s ambitions were enabled with Arm’s Cortex-M3 and NIC-400.
Arm Research are investigating a hardware-software codesign solution to support auto-vectorization, called Speculative Vectorization with Selective Replay.