- Adaptive computing makes robots more efficient
- AMD and ECARX to collaborate on immersive digital cockpit in-vehicle computing platform for next-generation electric vehicles
- Chipmakers warn that the chip boom is over and manufacturers frantic stockpiling is partly to blame
- Clearpath simplifies ROS integration with its mobile robots
- Semiconductor market to dip 2.5% next year as inflation hits
- Meet the Omnivore: developer builds bots with NVIDIA Omniverse and Isaac Sim
- How sensor fusion is driving vehicle autonomy forward
- Efinix offers 3x better logic density FPGA for embedded computing
- Getting Started with the Deep Learning Accelerator on NVIDIA Jetson Orin
Source: MV Pro Media, August 2, 2022 
A new generation of computing platforms, better suited to the demands of robotics, is now emerging. These platforms comprise heterogeneous processing elements that allow roboticists to build flexible compute architectures. Common problems include time inefficiencies, excessive power consumption, and security issues.
AMD and ECARX to collaborate on immersive digital cockpit in-vehicle computing platform for next-generation electric vehicles
Source: AMD, August 4, 2022 
ECARX is a global mobility tech company. The companies will work together on an in-vehicle computing platform for next-generation electric vehicles. The digital cockpit will launch with advanced features including heads-up display, rear seat entertainment, voice recognition and high-end gaming.
Source: Fortune, July 15, 2022 
TSMC reported a record 76.4% increase in second-quarter profit year on year. Chipmakers' fortunes rose in the early days of the pandemic as demand for electronics from stuck-at-home consumers and reduced supply made the semiconductor one of the hottest products on planet Earth.
Source: The Robot Report, July 29, 2022 
Clearpath Robotics has released new Robot Operating System (ROS) tools for its mobile robots. The company said the tools make it easier for ROS developers to get started with and use its robots. Clearpath also produced enhanced diagnostics manuals and Dingo test scripts.
Source: The Register, July 27, 2022 
Gartner downgrades its revenue growth forecast for the semiconductor industry. Rising inflation and consumers cutting back on spending take a greater toll on demand. Gartner estimates revenue of $639.2 billion this year, up from $594.8 billion last, but down from 26.3 percent growth in 2021.
Source: NVIDIA Blog, August 1, 2022 
Applied robotics Ph.D. student Antonio Serrano-Muñoz creates an Omniverse Extension to use Robot Operating System software with NVIDIA Isaac Sim.
Source: Newsroom, June 7, 2022 
As ADAS technology extends to critical, time-sensitive applications such as emergency braking, front collision warning and avoidance, and blind spot detection combining data from multiple sensors enables reliable, real time decisions for safer autonomous drivin
Source: Embedded, August 3, 2022 
Efinix has launched the latest FPGA in its Titanium family. New device features a hardened LPDDR4 interface for good bandwidth to external memory. A Linux capable quad-core RISC-V processor makes the Ti180 appropriate for high-performance embedded computing.
Source: NVIDIA Technical Blog, July 29, 2022 
Jetson combines a CPU and GPU into a single module that can be deployed at the edge. Jetson also features a variety of other processors, including hardware accelerated encoders and decoders. The Deep Learning Accelerator (DLA) is available on several Jetson-based platforms.
Source: Communications of the ACM, December 1, 2021 
In the field of artificial intelligence (AI) tooling has played a disproportionately large role in deciding which ideas succeed and which fail. This is because it adds noise to the marketplace of ideas and often means there is inertia in recognizing promising directions of research, an article posits.
FSHMEM: supporting partitioned global address space on FPGAs for large-scale hardware acceleration infrastructure
Source: arxiv, July 11, 2022 
Partitioned Global Address Space (PGAS) has become one of the most promising parallel computing models. FPGA is getting attention as an alternative compute platform for HPC systems. FSHMEM is a software/hardware framework that enables PGAS programming on FPGAs.
Hardware Acceleration in Robotics Newsletters
- Hardware Acceleration in Robotics #20 - Acceleration Robotics and Harvard present collaborative research, Robotics hiring levels in the tech industry rose in June 2022 and more
- Hardware Acceleration in Robotics #19 - ABB: 62% of US businesses looking to invest in robotics, Sony making sensors for autonomous vehicles and more
- Hardware Acceleration in Robotics #18 - EFPGAs bring a 10X advantage in power and cost, Introducing QODA: the platform for hybrid quantum-classical computing and more
- Hardware Acceleration in Robotics #17 - ROS2 HAWG #10, Siemens and NVIDIA to enable industrial metaverse, Simplifying hardware acceleration for robots with ROS2 and more
- Hardware Acceleration in Robotics #16 - RTI improves ROS2 performance in software-defined cars, Intel is running rings around AMD and Arm at the edge and more
- Hardware Acceleration in Robotics #15 - The ROS 2 hardware acceleration stack and ROBOTCORE™, RISC-V shines at embedded world with new specs and processors and more
- Hardware Acceleration in Robotics #14 - Acceleration Robotics launch ROBOTCORE™ to speed-up ROS 2 robots, ROS 2 driver now available for ABB’s robot arms and more
- Hardware Acceleration in Robotics #13 - Three architectures that power the robotic, Festo collaborates with Isaac Sim on industrial automation, Apple announces the M2 and more
- Hardware Acceleration in Robotics #12 - ROS 2 HAWG #9, ROS developers choice awards, NVIDIA increases the power of Arm CPUs and Omniverse software and more
ROS 2 Hardware Acceleration Working Group meetings
- Hardware Acceleration WG, meeting #10
- Hardware Acceleration WG, meeting #9
- Hardware Acceleration WG, meeting #8
- Hardware Acceleration WG, meeting #7
- Hardware Acceleration WG, meeting #6
- Hardware Acceleration WG, meeting #5
- Hardware Acceleration WG, meeting #4
- Hardware Acceleration WG, meeting #3
- Hardware Acceleration WG, meeting #2
- Hardware Acceleration WG, meeting #1
Williams, M. (2022, August 2). Adaptive computing makes robots more efficient. MV Pro Media. https://www.mvpromedia.com/adaptive-computing-makes-robots-more-efficient/ ↩︎
AMD and ECARX to collaborate on immersive digital cockpit in-vehicle computing platform for next-generation electric vehicles. (2022, August 4). AMD. https://www.amd.com/en/press-releases/2022-08-04-amd-and-ecarx-to-collaborate-immersive-digital-cockpit-vehicle-computing ↩︎
Gordon, N. (2022, July 15). HTTPS://fortune-com.cdn.ampproject.org/C/S/fortune.com/2022/07/15/tsmc-q2-2022-earnings-chip-shortage-boom-excess-inventory-stockpile/amp/. Fortune. https://fortune-com.cdn.ampproject.org/c/s/fortune.com/2022/07/15/tsmc-q2-2022-earnings-chip-shortage-boom-excess-inventory-stockpile/amp/ ↩︎
Wessling, B. (2022, July 29). Clearpath simplifies ROS integration with its mobile robots. The Robot Report. https://www.therobotreport.com/clearpath-simplifies-ros-integration-with-its-mobile-robots/ ↩︎
Robinson, D. (2022, July 27). Semiconductor market to decline 2.5 percent in 2023: Gartner. The Register: Enterprise Technology News and Analysis. https://www.theregister.com/2022/07/27/semiconductor_market_gartner_report/?utm_source=daily&utm_medium=newsletter&utm_content=article ↩︎
Lee, A. (2022, August 1). Meet the omnivore: Developer builds bots with NVIDIA Omniverse and Isaac Sim. NVIDIA Blog. https://blogs.nvidia.com/blog/2022/08/01/omniverse-developer-antonio-serrano-munoz/ ↩︎
How sensor fusion is driving vehicle autonomy forward. (2022, June 7). Newsroom | news.ti.com. https://news.ti.com/blog/2022/06/07/how-sensor-fusion-is-driving-vehicle-autonomy-forward?HQS=asc-null-null-adas_autobrand_da22_adassensing-enslt-blog-AAC_0729-eu_awr&DCM=yes&dclid=CMLqsJDirPkCFcKc1QodjrcGwQ ↩︎
Dahad, N. (2022, August 3). Efinix offers 3x better logic density FPGA: Embedded.com. Embedded.com. https://www.embedded.com/efinix-offers-3x-better-logic-density-fpga-for-embedded-computing/ ↩︎
Welsh, J. (2022, July 29). Getting started with the deep learning accelerator on NVIDIA Jetson Orin. NVIDIA Technical Blog. https://developer.nvidia.com/blog/getting-started-with-the-deep-learning-accelerator-on-nvidia-jetson-orin/ ↩︎
Hooker, S. (2021, December 1). The hardware lottery. Communications of the ACM. https://cacm.acm.org/magazines/2021/12/256929-the-hardware-lottery/fulltext ↩︎
Arthanto, S. F., Ojika, D., & Kim, J. Y. (2022, July 11). FSHMEM: supporting partitioned global address space on FPGAs for large-scale hardware acceleration infrastructure. arxiv.org. https://arxiv.org/pdf/2207.04625.pdf ↩︎