Antmicro · Open Source Jetson Baseboard
OPEN SOURCE JETSON BASEBOARD| antmicro.com
Kenning is Antmicro’s library aiming to simplify the workflow with machine learning applications on edge devices. It is used for testing and deploying ML pipelines on a variety of embedded platforms regardless of the underlying framework. Based on a variety of practical edge AI use cases that we are working with on a daily basis, we have now expanded its functionality to include an environment that will help with development of final applications. Expanding the use case beyond just testing ...| antmicro.com
As we continue our push for more software-driven hardware development as part of our work within CHIPS Alliance and RISC-V, we see an increasing need for scalable and flexible CI solutions that can be used with a mix of open source and proprietary components. By building on top of existing infrastructure such as GCP, GH Actions and Terraform, it’s possible to achieve noticeable performance gains, better traceability and runtime isolation for some of the advanced use cases we are helping our...| antmicro.com
We are often approached by customers who want to build a high-performance, user-facing industrial device (like a smart kiosk, machine control screen or vehicle dashboard), and their obvious reference is the Android smartphone in their pocket. Using Android is a natural thought, as it provides a familiar user interface in otherwise complex and data-heavy environments.| antmicro.com
Renode is an open source simulation framework enabling effortless and collaborative software development of embedded and IoT devices in a deterministic environment. A wide toolbox of features for debug, trace and experimentation make it extremely useful in interactive code development scenarios, but the full potential of the tool is revealed in a Continuous Integration environment. With Antmicro’s help, a number of organizations are currently adopting Renode to radically improve their testi...| antmicro.com
Continuous Integration and smart lifecycle management are key for high-tech product development, which is often a complex and multi-faceted process that requires automation to be efficient and failure-proof. At Antmicro, we’ve been creating various open source cloud and hybrid cloud solutions for our customers, helping them to encapsulate the complexity of their software stack. Lots of those projects cross the hardware/software boundary and involve a mix of open source and proprietary code,...| antmicro.com
Antmicro helps its customers build complex FPGA and ASIC RISC-V systems based on open source building blocks such as those provided by the OpenTitan Root of Trust project. The AMD-Xilinx Kintex-7 is a relatively inexpensive and obtainable commodity FPGA family which makes it an excellent prototyping and research platform that is possible to replicate at scale.| antmicro.com
With Moore’s law no longer to be taken for granted, there’s a real need to find new ways to scale compute capability to keep up with the ever increasing demand. Antmicro is helping customers tackle this problem on multiple levels, developing distributed, edge computing systems to bring processing closer to the data sources, and building new, collaborative methodologies and open source building blocks for ASIC and FPGA as part of RISC-V and CHIPS Alliance. There is also the most obvious me...| antmicro.com
As part of our open source-centric strategy, Antmicro has been developing open source hardware which serves as a base for rapidly developing new, complex solutions - and our customers often reach out to us to lend them our expertise in building custom platforms and adapting them to their needs. In this spirit, for many years now we have been perfecting our original Jetson Nano Baseboard, a miniature edge AI platform aimed at pushing forward the NVIDIA-centric edge AI ecosystem, and this board...| antmicro.com
Creating Machine Learning models for deployment on constrained devices requires a considerable number of manual tweaks. Developers need to take into account the size and compute constraints of the target platform to adjust the architecture, as well as search for optimal training hyperparameters. These include learning rate, regularizations, optimizer and its parameters, as well as datasets, optimal model compression configuration and more. The AI-specific expertise these steps require also ma...| antmicro.com
AI algorithms often require significant processing power typically associated with data centers. However, privacy concerns, latency and security considerations, together with increased compute capabilities of edge devices, are making local AI data preprocessing increasingly common.| antmicro.com
Antmicro has been working with a large number of customers implementing AI software on embedded systems, helping utilize all the advantages of an open source-based approach. To achieve this we created a complete methodology around open source tools - a lot of which are indeed of our own design - that allows us to build reproducible, production ready embedded software for customers across numerous verticals. In complex edge AI projects, this often involves developing CI systems that can build ...| antmicro.com
Antmicro’s open source simulation framework, Renode, was built to enable simulating real-life scenarios - which have a tendency to be complex and require hybrid approaches.| antmicro.com
FastVDMA is an open source DMA (Direct Memory Access) controller developed at Antmicro.| antmicro.com
The PolarFire SoC from our partner Microchip is the first mass-market Linux-capable implementation of RISC-V and the early access release of the Icicle development kit is huge news in the RISC-V world. Although this exciting 4+1 core FPGA SoC is becoming physically available only now, we have been collaborating with Microchip (then Microsemi) around this FPGA SoC since as early as 2017, enabling support for it in our Renode simulation platform. It is all the more exciting to see it in real li...| antmicro.com
Originally issued by QuickLogic, the following press release announces the QORC initiative and describes Antmicro’s contribution.| antmicro.com
NVIDIA’s edge computing hardware has been a part of Antmicro’s open hardware platform development throughout all of its generations. This legacy of facilitating proof-of-concept prototyping using open source designs has resulted in our ever-expanding, open ecosystem of hardware platforms, with the NVIDIA Jetson Nano/Xavier NX baseboard leading the way as the most popular example.| antmicro.com
The demand for deploying machine learning models, especially state-of-the-art deep neural networks on edge devices is rapidly growing. Edge AI allows to run inference locally, without the need for a connection to the cloud, which makes the technologies more portable and self-sufficient. Without the need for sending the data to the cloud, edge AI solutions are also much safer in terms of data privacy.| antmicro.com
Co-simulating HDL has been possible in Renode since the 1.7.1 release, but the functionality - critical for hardware/software co-development as well as FPGA use cases - is constantly evolving based on the needs of our customers like Google and Microchip as well as our work in open source groups including CHIPS Alliance and RISC-V International. To quickly recap, by co-simulation we mean a scenario where a part of the system is simulated in Renode but some specific peripheral or subsystem is s...| antmicro.com
We are happy to announce our involvement in ‘Very Efficient Deep Learning in IoT’ (VEDLIoT) - a project funded by the European Commission and coordinated by Bielefeld University’s CoR-Lab, launched at the end of 2020. Comprising a 12-member international research group, VEDLIoT aims to develop a next-generation software/hardware platform for the Internet of Things. Antmicro’s contributions, among other things, will be to leverage its leading position in RISC-V, machine learning and si...| antmicro.com
Customers interested in building new industrial or consumer devices, typically involving one or more PCBs and based on Linux, Zephyr or Android (or even all of them at the same time), often approach Antmicro before they know what exact components they want to use. Such projects typically begin with a block diagram, and interestingly, across the industry there is no unified and structured way to collaborate at this stage of the project, before an actual schematic of a system can be produced an...| antmicro.com
Based on internal R&D efforts, research projects like VEDLIoT and practical applications in a variety of customer cases, Antmicro is constantly working on improving Kenning, its open source framework for creating deployment flows and runtimes for Deep Neural Network applications on embedded hardware platforms. The AI toolkit is now gaining additional flexibility through highly customizable, modular blocks for developing real-time runtimes and automated search for best parameters for the optim...| antmicro.com
Many applications in the wild can be represented as graphs of interconnected nodes, especially when working with sets of modular blocks that can be connected with each other via certain APIs or interfaces. Such use cases are part of the many areas of Antmicro’s day-to-day work, for example:| antmicro.com
Antmicro’s Kenning framework, introduced during our work on the VEDLIoT edge AI research project, is being used in various local AI processing projects to create deployment flows and runtimes for Deep Neural Network applications on a variety of target hardware.| antmicro.com
Development of Machine Learning algorithms which enable new and exciting applications is progressing at a breakneck pace, and - given the long turnaround time of hardware development - the designers of dedicated hardware accelerators are struggling to keep up. FPGAs offer an interesting alternative to ASICs, enabling a much faster and more flexible environment for such HW-SW co-development - and with projects such as the FPGA interchange format, Antmicro has been turning the FPGA ecosystem to...| antmicro.com
Kenning helps develop real-world Machine Learning solutions for ARM and RISC-V platforms such as NVIDIA Jetson AGX Orin, Google Coral or HiFive Unmatched by seamlessly interconnecting different underlying optimization and deployment frameworks and creating rich reports on model quality and performance, like in the recently described industrial use case. The latest developments extend Kenning’s applicability to two new domains, adding bare-metal runtimes for non-Linux targets and integration...| antmicro.com
In the process of building their next-gen products, customers who want complete control, transparency and customization often contract Antmicro to develop complex hardware designs, including application SoC baseboards or high-end FPGA-based ASIC prototyping boards. Through our numerous ecosystem-focused collaborations and extensive R&D we have been able to release a wide variety of open hardware designs, which often become the base for subsequent, even more advanced projects. But Antmicro’s...| antmicro.com
