The Arm Machine Learning processor provides up to 4.6 Trillions of Machine Learning Operations Per Second, as part of the Project Trillium, Arm’s Machine Learning (ML) platform, enables a new era of advanced, ultra-efficient inference at the edge with Programmable layer engines for future-proofing, Highly tuned for advanced geometry implementations, Specifically designed for ML and neural network (NN) capabilities, the architecture is versatile enough to scale to any device, from IoT to connected cars and servers.
Built from the ground up for optimal performance and efficiency, Project Trillium completes the Arm Heterogenous ML compute platform with the Arm ML processor, the second-generation Arm Object Detection (OD) processor and open-source Arm NN software.
The Arm Machine Learning processor consists of state-of-the-art optimized fixed-function engines that provide best-in-class performance within a constrained power envelope. Additional programmable layer engines support the execution of non-convolution layers, and the implementation of selected primitives and operators, along with future innovation and algorithm generation. The network control unit manages the overall execution and traversal of the network and the DMA moves data in and out of the main memory. Onboard memory allows central storage for weights and feature maps, thus reducing traffic to the external memory and therefore, power.
At the 2017 IET Christmas Lecture, Hub Mentor and pioneering technology entrepreneur Sir Robin Saxby, founding CEO and Chairman of ARM Holdings (who I interviewed here) shares his advice for growing a start-up with limited resources into a global powerhouse. Under his leadership, ARM became the world’s leading semiconductor Intellectual Property (IP) company, and now connects over 5 billion people, powering everything from supercomputers to each Whatsapp message on your phone.
[You can auto-translate the english subtitles to any language from YouTube on a desktop, the video is also available with only external subtitles here]
He answers questions like:
How can a small start-up compete with far bigger competition?
How do you build the right team?
What is the most common mistake technical founders make?
Sir Robin continues to champion entrepreneurship in the UK, and is a committed supporter of the Royal Academy of Engineering’s Enterprise Hub (https://enterprisehub.raeng.org.uk/)
Exciting Liverpool Technology start up:
Robin and Friends Bandcamp
Participated in creating this video:
Jan Mary Baloyo, IET
Nilar Shyun Mya, IET PSB Academy On Campus
Syafiq Shahul, IET PSB Academy On Campus
Stanley Liau, IET Singapore LN
Overview of Arm
• HPC engagements
Arm partner information
• Latest deployment information
Arm Software Ecosystem
• Software stack enabling
• Arm's priorities on libraries and applications,
Filmed at the Arm HPC User Group at SC17 in Denver.
The Mont-Blanc European Exascale supercomputing project based on ARM power-efficient technology, using Cavium ThunderX2 ARM server processor to power its new High Performance Computing (HPC) prototype with HPC SW infrastructure for ARM with tools, code stacks and libraries and more. The ambition of the Mont-Blanc project is to define the architecture of an Exascale-class compute node based on the ARM architecture, and capable of being manufactured at industrial scale. The Mont-Blanc 3 system being built by a consortium which includes Atos, ARM, AVL (Austrian power train developer) and seven academic institutions, including the Barcelona Supercomputer Center (BSC), implements this ARM for HPC with high memory bandwidth and high core count on Cavium's custom ARMv8 core architecture with out-of-order execution that can run at 3 GHz. The ThunderX2 might be delivering twice the integer and floating point performance compared with ThunderX1 with also twice the memory bandwidth.
Filmed in 4K60 at Supercomputing 2017 in Denver using Panasonic GH5 ($1999 at Amazon.com) on firmware 2.1 (aperture priority, AF continuous tracking) with Leica 12mm f1.4 ($1297 at Amazon.com) with Sennheiser MKE440 stereo shotgun microphone ($325 at Amazon.com), get $25 off renting cameras and lenses with my referral link at https://share.lensrentals.com/x/wWbHqV
Grant Likely has built a custom video-game arcade machine with colorful control buttons and mouse for using with classic arcade game emulators, all Open Source and Open Hardware, with the source code up on GitHub with some links up at http://www.secretlab.ca/archives/240 you can also watch his Arcade assembly time lapse video. Filmed at the Linaro Connect San Francisco 2017.
ARM shows their HDR to SDR conversion processed with their adaptive local tone mapping engine to achieve a dynamic range compression to show HDR content at the highest quality on a regular SDR display. Filmed at the SID Display Week.
ARM Innovation Ecosystem Accelerator (“ARM Accelerator”) is an international global startup accelerator recruitment network in Mainland China, UK, U.S, Israel, Canada, France, Hong Kong, and Taiwan area, helping startups accelerate development in areas such as VR/AR, Robotics/AI, Smart Car, Smart Healthcare, Smart Home, Smart City. ARM Accelerator is an innovation and acceleration platform featured among ARM's ecosystem. ARM Accelerator focuses on smart hardware and IoT ecosystem. The core advantage of ARM Accelerator is to create an one-stop platform for China and overseas startups and integrates the world-leading IC design companies and scarce, high-value labs to provide the customers all kinds of incubation and acceleration services, such as professional technology consulting, design service, and global promotion and investment matchmaking.
Keynote at the Computex 2017 CPX Conference by Rene Haas, ARM President, Intellectual Property Group.
ARM Media Processing Group VP, GM and Fellow, Jem Davies announces the ARM Mali-G72 GPU for Machine Learning, VR & High Fidelity Mobile Gaming. 1 billion Mali-based chips were shipped in 2016, With 1.4x the performance of last year's ARM Mali-G71 GPU, 17% more performance in machine learning (ML) efficiency, for local offline GPU compute computer vision facilitated by ALU and data path improvements to reduce energy consumed by data movements with 25% higher energy efficiency and 20% better area efficiency, with multiple Bifrost optimizations including increased tile buffer memory, tiler scalability and L1 cache.
For faster ARM Powered laptops, smartphones, servers and more, Nandan Nayampally, GM & VP of ARM’s Compute Processing Group announces the ARM Cortex-A75 and ARM Cortex-A55, the new fastest performance, most power efficient ARM designs for high end performance and for mid-range to entry level processing, the first processors launched on ARM DynamIQ technology, designed from the ground up for AI improvements, low latency, acceleration connections, ARM Cortex-A75 delivers 50% improvement in raw integer performance, even greater gains for specialized workloads at given nanometer manufacturing, with these also working even better on newer smaller nanometer manufacturing making these all that faster. ARM Cortex-A75's new performance enables faster ARM Powered Laptops and Smartphones with faster performance and better power efficiency, also suitable for infrastructure (servers, networking, more) and self driving cars and other uses in the automotive industry. ARM Cortex-A55 provides the new LITTLE to Cortex-A75’s big, with 2.5x the power efficiency of its predecessor, bringing performance to the edge across a variety of applications and performance points from IOT edge gateways to mainstream. Combining the two new CPUs in a DynamIQ big.LITTLE cluster gives you multiple configurations, and specifically doubles performance in a 1+7 configuration for example.