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Addressing the hardware supply chain security challenge

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? (read more)

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SMARTER: How can edge computing support shared infrastructure?

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.(read more)

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Arm Research’s collaboration with the Cambridge ELLIS Unit

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

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What you missed at the second On-Device Intelligence Workshop

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. (read more)

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Improving federated learning with dynamic regularization

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.(read more)

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Eliminating memory barriers with the Execution Dependence Extension

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

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Engineering a career as a woman in technology 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.(read more)

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Neural network architectures for deploying TinyML applications on commodity...

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

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Buried interconnects for signal routing

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

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PlasticArm: Realizing the full potential of the Internet of Things

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...

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Scalable MTJ simulation: Reliable and efficient compact models

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. (read more)

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Scalable MTJ simulation: How to efficiently analyze stochasticity in MRAM (2/2)

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

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FixyFPGA: Fully-parallel and fully-pipelined FPGA accelerator for sparse CNNs

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...

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Fast power-modelling for accurate CPU power-introspection

APOLLO achieves fast, yet accurate power-modelling for both design- and runtime power-introspection within the same unified framework.(read more)

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Radar SoC: detected at the cutting-edge

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.(read more)

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Speculative Vectorization with Selective Replay

Arm Research are investigating a hardware-software codesign solution to support auto-vectorization, called Speculative Vectorization with Selective Replay.(read more)

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Smart Atomic Memory Operations and Advanced Sparse Data Structures at BSC

Read about two Arm-sponsored PhD students and their work into Smart Atomic Memory Operations and Advanced Sparse Data Structures at the Arm-BSC Centre of Excellence. (read more)

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Fast and accurate keyword spotting using Transformers

On-device automatic speech recognition is now becoming feasible and is useful in scenarios without internet connection or when data privacy is a concern.(read more)

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Sparking potential for community development: Arm Education Kits now...

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

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SpiNNaker: Next-level thinking

SpiNNaker1 connected a million mobile phone processors, operating in some ways like a brain. SpiNNaker2 will drive the next generation of AI. (read more)

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