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ARM

www.arm.com

ARM designs the technology that is at the heart of advanced digital products, from wireless, networking and consumer entertainment solutions to imaging, automotive, security and storage devices. ARM’s comprehensive product offering includes RISC microprocessors, graphics processors, video engines, enabling software, cell libraries, embedded memories, high-speed connectivity products, peripherals and development tools. Combined with comprehensive design services, training, support and maintenance, and the company’s broad Partner community, they provide a total system solution that offers a fast, reliable path to market for leading electronics companies.

Recent Content by Company

New AI Technology from Arm Delivers Unprecedented On-device Intelligence for IoT

Arm launches industry’s first microNPU for Cortex-M combined with newest Cortex-M processor to securely deliver up to a 480x uplift in ML performance New IP will enable AI everywhere on billions of next-generation smaller, power-constrained devices with greater on-device ML processing Software development flow specifically optimized for developer productivity and maximizing ML performance across all …

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New Arm IP Brings Intelligent, Immersive Experiences to Mainstream Markets

News Highlights: Arm Ethos-N57 and Ethos-N37 NPUs; extending the range of Arm Machine Learning (ML) processors to enable Artificial Intelligence (AI) applications in mainstream devices Arm Mali-G57 GPU; the first mainstream Valhall architecture-based GPU delivering 1.3x better performance over previous generations Arm Mali-D37 DPU; delivering a rich display feature set within the smallest area for …

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“Performance Analysis for Optimizing Embedded Deep Learning Inference Software,” a Presentation from Arm

Gian Marco Iodice, Staff Compute Performance Software Engineer at Arm, presents the "Performance Analysis for Optimizing Embedded Deep Learning Inference Software" tutorial at the May 2019 Embedded Vision Summit. Deep learning on embedded devices is currently enjoying significant success in a number of vision applications—particularly smartphones, where increasingly prevalent AI cameras are able to enhance …

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NVIDIA Brings CUDA to Arm, Enabling New Path to Exascale Supercomputing

Global HPC Leaders Join to Support New Platform June 17, 2019 — International Supercomputing Conference — NVIDIA today announced its support for Arm CPUs, providing the high performance computing industry a new path to build extremely energy-efficient, AI-enabled exascale supercomputers. NVIDIA is making available to the Arm® ecosystem its full stack of AI and HPC software — …

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Delivering Next-generation AI Experiences for the 5G World

News Highlights: Arm Cortex-A77 CPU: redefining mobile performance with 20% IPC improvements Arm Mali-G77 GPU: all new Valhall architecture for premium mobile experiences, delivering high-end graphics at increased efficiency Arm Machine Learning (ML) processor: delivering best-in-class efficiency with up to 5 TOPs/W and a robust software ecosystem May 27, 2019 – Over the past 12+ months …

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Next-generation Armv8.1-M Architecture: Delivering Enhanced Machine Learning and Signal Processing for the Smallest Embedded Devices

February 14, 2019 – News highlights: Arm Helium technology is a new M-Profile Vector Extension bringing enhanced compute capabilities to the Armv8.1-M architecture Delivering up to 15x performance uplift for machine learning and up to 5x uplift to signal processing tasks on the smallest of edge devices For next-generation Cortex-M processors, aimed at small, embedded …

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A Sharper Digital Eye For Intelligent Devices With the Latest Arm ISP Technology

January 03, 2019 – News highlights New Arm Mali-C52 and Mali-C32 image signal processors (ISPs) provide class-leading image quality, a complete software package, and full set of calibration and tuning tools Higher image quality in a wide range of everyday devices including drones, smart home assistants and security, and internet protocol (IP) cameras New applications …

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Arm Demonstration of Image Classification Using Arm NN and the Compute Library

Gian Marco Iodice, Senior Software Engineer at Arm, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Iodice demonstrates image classification using Arm NN and the Compute Library, showing how they provide Arm-based platforms with the flexibility to switch between the CPU and GPU for easy and performant image classification.

Arm Demonstration of the Company’s Object Detection Processor

Alexey Lopich, Principal Hardware Engineer and Team Lead at Arm, delivers a product demonstration at the May 2018 Embedded Vision Summit. Specifically, Lopich demonstrates Arm’s Object Detection processor, showing how it detects objects – from 50×60 pixels to full screen – in real time, at high speed (60fps) and in high resolution (Full HD). He …

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“Deep Learning on Arm Cortex-M Microcontrollers,” a Presentation from Arm

Vikas Chandra, Senior Principal Engineer and Director of Machine Learning at Arm, presents the “Deep Learning on Arm Cortex-M Microcontrollers” tutorial at the May 2018 Embedded Vision Summit. Deep learning algorithms are gaining popularity in IoT edge devices due to their human-level accuracy in many tasks, such as image classification and speech recognition. As a …

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“Project Trillium: A New Suite of Machine Learning IP,” a Presentation from Arm

Steve Steele, Director of Platforms in the Machine Learning Group at Arm, presents the “Project Trillium: A New Suite of Machine Learning IP from Arm” tutorial at the May 2018 Embedded Vision Summit. Machine learning processing engines today tend to focus on specific device classes or the needs of individual sectors. Arm’s Project Trillium changes …

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“Even Faster CNNs: Exploring the New Class of Winograd Algorithms,” a Presentation from Arm

Gian Marco Iodice, Senior Software Engineer in the Machine Learning Group at Arm, presents the “Even Faster CNNs: Exploring the New Class of Winograd Algorithms” tutorial at the May 2018 Embedded Vision Summit. Over the past decade, deep learning networks have revolutionized the task of classification and recognition in a broad area of applications. Deeper …

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“Computer Vision on ARM: Faster Ways to Optimize Software for Advanced Mobile Computing Platforms,” a Presentation from ARM

Roberto Mijat, Director of Software Product Management in the Business Segment Group at ARM, presents the "Computer Vision on ARM: Faster Ways to Optimize Software for Advanced Mobile Computing Platforms" tutorial at the May 2017 Embedded Vision Summit. Mobile computing platforms are ubiquitous, and therefore provide an exciting vehicle for the deployment of new computer …

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“This Changes Everything — Why Computer Vision Will Be Everywhere,” a Presentation from ARM

Tim Ramsdale, General Manager of the Imaging and Vision Group at ARM, presents the "This Changes Everything — Why Computer Vision Will Be Everywhere" tutorial at the May 2017 Embedded Vision Summit. Computer vision, or teaching machines to see, will be revolutionary – it will change everything. Beyond the obvious markets where it is having …

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Accelerating AI Experiences from Edge to Cloud

First processors based on ARM DynamIQ technology take a big step towards boosting AI performance by more than 50x over the next 3-5 years ARM Cortex-A75 delivers massive single-thread compute uplift for premium performance points ARM Cortex-A55 is the world’s most versatile high-efficiency processor ARM Mali-G72 GPU expands VR, gaming and Machine Learning capabilities on premium …

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“Computer Vision on ARM: The Spirit Object Detection Accelerator,” a Presentation from ARM

Tim Hartley, Senior Product Manager in the Imaging and Vision Group at ARM, presents the "Computer Vision on ARM: The Spirit Object Detection Accelerator" tutorial at the May 2017 Embedded Vision Summit. In 2016, ARM released Spirit, a dedicated object detection accelerator, bringing industry-leading levels of power- and area-efficiency to computer vision workflows. In this …

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“Using SGEMM and FFTs to Accelerate Deep Learning,” a Presentation from ARM

Gian Marco Iodice, Software Engineer at ARM, presents the "Using SGEMM and FFTs to Accelerate Deep Learning" tutorial at the May 2016 Embedded Vision Summit. Matrix Multiplication and the Fast Fourier Transform are numerical foundation stones for a wide range of scientific algorithms. With the emergence of deep learning, they are becoming even more important, …

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“Lessons Learned from Bringing Mobile and Embedded Vision Products to Market,” a Presentation from ARM

Tim Hartley, Product Manager in the Personal Mobile Compute Business Line at ARM, presents the "Lessons Learned from Bringing Mobile and Embedded Vision Products to Market" tutorial at the May 2016 Embedded Vision Summit. Great news: technology is finally at a point where we can build sophisticated computer vision applications that run on mass market …

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Optimizing Computer Vision Applications Using OpenCL and GPUs

The substantial parallel processing resources available in modern graphics processors makes them a natural choice for implementing vision-processing functions. The rapidly maturing OpenCL framework enables the rapid and efficient development of programs that execute across GPUs and other heterogeneous processing elements within a system. In this article, we briefly review parallelism in computer vision applications, …

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Optimizing Fast Fourier Transformation on ARM Mali GPUs

This article was originally published at ARM's website. It is reprinted here with the permission of ARM. The Fast Fourier Transformation (FFT) is a powerful tool in signal and image processing. One very valuable optimization technique for this type of algorithm is vectorization. This article discusses the motivation, vectorization techniques and performance of the FFT …

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Speeding Up the Fast Fourier Transform Mixed-Radix on Mobile ARM Mali GPUs By Means of OpenCL (Part 3)

This article was originally published at ARM's website. It is reprinted here with the permission of ARM. For more information, please see ARM's developer site, which includes a variety of GPU Compute, OpenCL and RenderScript tutorials. In this third and last part of this blog series we are going to extend the mixed-radix FFT OpenCL™ …

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Speeding Up the Fast Fourier Transform Mixed-Radix on Mobile ARM Mali GPUs By Means of OpenCL (Part 2)

This article was originally published at ARM’s website. It is reprinted here with the permission of ARM. For more information, please see ARM’s developer site, which includes a variety of GPU Compute, OpenCL and RenderScript tutorials. Here we are for the second part of our blog series about the OpenCL™ implementation of Complex to Complex …

Speeding Up the Fast Fourier Transform Mixed-Radix on Mobile ARM Mali GPUs By Means of OpenCL (Part 2) Read More +

Speeding Up the Fast Fourier Transform Mixed-Radix on Mobile ARM Mali GPUs By Means of OpenCL (Part 1)

This article was originally published at ARM's website. It is reprinted here with the permission of ARM. For more information, please see ARM's developer site, which includes a variety of GPU Compute, OpenCL and RenderScript tutorials. This is the first article of three that will focus on the implementation of Fast Fourier Transform (FFT) using …

Speeding Up the Fast Fourier Transform Mixed-Radix on Mobile ARM Mali GPUs By Means of OpenCL (Part 1) Read More +

“Using Vision to Create Smarter Consumer Devices with Improved Privacy,” a Presentation from Apical

Michael Tusch, Founder and CEO of Apical, presents the "Using Vision to Create Smarter Consumer Devices with Improved Privacy" tutorial at the May 2015 Embedded Vision Summit. Machines are valuable primarily due to their ability interact with people and with the physical world. But today, most of the consumer devices in the “Internet of Things” …

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“Understanding the Role of Integrated GPUs in Vision Applications,” a Presentation from ARM

Roberto Mijat, Visual Computing Marketing Manager at ARM, presents the "Understanding the Role of Integrated GPUs in Vision Applications" tutorial at the May 2015 Embedded Vision Summit. Today, systems-on-chip (SoCs) used in applications such as smart TVs, smartphones and tablets typically include a multi-core CPU with single-instruction, multiple-data capabilities as well as a GPU that …

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Realizing the Benefits of GPU Compute for Real Applications with Mali GPUs

This article was originally published at ARM's Community site. It is reprinted here with the permission of ARM. I have just returned from a fortnight spent hopping around Asia in support of a series of ARM hosted events we call the Multimedia Seminars, which took place in Seoul (27th June), Taipei (1st July) and Shenzhen …

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October 2013 Embedded Vision Summit Technical Presentation: “Better Image Understanding Through Better Sensor Understanding,” Michael Tusch, Apical

Michael Tusch, Founder and CEO of Apical Imaging, presents the "Better Image Understanding Through Better Sensor Understanding" tutorial within the "Front-End Image Processing for Vision Applications" technical session at the October 2013 Embedded Vision Summit East. One of the main barriers to widespread use of embedded vision is its reliability. For example, systems which detect …

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April 2013 Embedded Vision Summit Technical Presentation: “Exploiting Synergy Between Image Improvement and Image Understanding Algorithms,” Michael Tusch, Apical

Michael Tusch, founder and CEO of Apical, presents the "Exploiting Synergy Between Image Improvement and Image Understanding Algorithms" tutorial within the "Image Sensors and Front-End Image Processing" technical session at the April 2013 Embedded Vision Summit.

September 2012 Embedded Vision Summit Discussion Panel: Apical, National Instruments, and VanGogh Imaging

Jeff Bier, Embedded Vision Alliance Founder, moderates a discussion panel comprised of the presenters in the "Using Processors for Embedded Vision" technical session at the September 2012 Embedded Vision Summit; Michael Tusch from Apical, Kamalina Srikant from National Instruments, and Ken Lee from VanGogh Imaging. The panelists discuss topics such as processing partitioning in heterogeneous …

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September 2012 Embedded Vision Summit Presentation: “Harnessing Hardware Accelerators to Move from Algorithms to Embedded Vision,” Michael Tusch, Apical

Michael Tusch, founder and CEO of Apical, presents the "Harnessing Hardware Accelerators to Move from Algorithms to Embedded Vision" tutorial within the "Using Processors for Embedded Vision" technical session at the September 2012 Embedded Vision Summit. The presentation focuses on the programming challenges associated with implementing vision algorithms efficiently on embedded devices with a degree …

September 2012 Embedded Vision Summit Presentation: “Harnessing Hardware Accelerators to Move from Algorithms to Embedded Vision,” Michael Tusch, Apical Read More +

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Image Sensors Evolve to Meet Emerging Embedded Vision Needs – Part 2: HDR Processing

by Michael Tusch Founder and CEO Apical Limited This article was originally published at EDN Magazine. It is reprinted here with the permission of EDN. It was adapted from Michael's technical article on the Embedded Vision Alliance website. Part 1 of this article looks at examples of embedded vision and how the technology transition from …

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HDR Sensors for Embedded Vision

By Michael Tusch Founder and CEO Apical Limited At the late-March 2012 Embedded Vision Alliance Summit, Eric Gregori and Shehrzad Qureshi from BDTI presented a helpful overview of CCD and CMOS image sensor technology. I thought it might be interesting to extend this topic to cover so-called HDR (High Dynamic Range) / WDR (Wide Dynamic …

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Dynamic Range And Edge Detection: An Example Of Embedded Vision Algorithms’ Dependence On In-Camera Image Processing

By Michael Tusch Founder and CEO Apical Limited This article will expand on the theme initiated in the premier article of this series, that of exploring how the pixel processing performed in cameras can either enhance or hinder the performance of embedded vision algorithms. Achieving natural or otherwise aesthetically pleasing camera images is normally considered …

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How Does Camera Performance Affect Analytics?

By Michael Tusch Founder and CEO Apical Limited Camera designers have decades of experience in creating image processing pipelines which produce attractive and/or visually accurate images, but what kind of image processing produces video which is well-purposed for subsequent analytics? It seems reasonable to begin by considering a conventional ISP (image signal processor). After all, …

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May 18 - 21, Santa Clara, California

The preeminent event for practical, deployable computer vision and visual AI, for product creators who want to bring visual intelligence to products.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

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