FPGA with Nvidia Jetson

NVIDIA Jetson is the leading Edge AI computing platform used by over a million developers and companies worldwide. With cloud support across all NVIDIA Jetson products, intelligent machine makers and AI-powered embedded systems developers are empowered to develop and deploy high-tech software functions to edge devices in areas such as industrial automation and roboticssmart cities, and smart agricultureIndustrial Internet of Things, and many others. In addition, cloud support enables manufacturers, service companies, and developers to regularly improve, improve accuracy, and add new features to Jetson-powered Edge AI.

Jetson solutions are supported by a single software stack, which allows us to deploy systems anywhere quickly. The Jetson platform is equipped with the Jetpack developer toolkit, which includes platform support, Linux OS, NVIDIA CUDA®, and is also compatible with other platforms. In addition, the DeepStream SDK allows developers to design and install Jetson-based video analytics systems quickly.

The NVIDIA platform covers all of the company’s solutions, from data center supercomputers to standalone Jetson devices. The toolkit for compact Jetson is not much different from what is for the usual desktop GPUs. However, the advantage of NVIDIA solutions is that they all support CUDA, and transferring code or part of the calculations from one device to another will not cause any difficulties. For example, we can train models in high-performance data centers on Tesla and implement them on compact Jetson.

NVIDIA Jetson – Enables us to build software-defined systems that use hardware-accelerated deep learning models. ShuraCore experts believe that all embedded and edge devices should not be highly specialized but customizable – so that by changing only the software part, it is possible to supplement and improve the functionality of the device as a whole. At the same time, we can focus on a different budget. For example, if Xavier is needed to solve the most complex problems, then the same Nano will provide inexpensive performance that is sufficient for analyzing several video streams simultaneously. All these devices use the same software, and only by changing the hardware solution can they get performance gains and expanding capabilities without having to redo the software code.

GPUs, with their colossal parallelism, are best suited for real-time video and signal processing. However, there is often no direct high-speed interface in a real-time system to signal sources such as cameras or sensors. For this task, a field-programmable gate array (FPGA) is ideal for capturing and preprocessing multiple video streams or high-speed sensor data in real-time. Besides dividing computational tasks between GPUs and FPGA, direct communication between GPUs and FPGA is a crucial issue in this design. However, since the CPU usually controls communication, this often becomes a system bottleneck. The bottleneck is eliminated by using GPUDirect RDMA technology.

AI Development Services

Tensorflow, PyTorch, Keras, Caffe, Darknet, MxNet

AI Development Services

Xilinx Machine Learning (ML) Suite, NVIDIA CUDA-X AI and CUDA, RadeonML and ROCm, OpenCL and OpenMP, OpenVINO
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Artificial intelligence, machine learning, and deep learning are integral parts of many enterprises, factories, and complex software. This terminology is often used synonymously. Artificial intelligence is making huge strides forward – from advances in self-driving vehicles and the ability to beat humans in games to automated customer service and full automation and decision-making in various industries.

Artificial Intelligence is a cutting-edge technology that is poised to revolutionize your business. Artificial intelligence development is also driving software development services, embedded software, IoT, and IIOT applications. Software developers are currently exploring new ways of programming that are more prone to deep learning and machine learning. ShuraCore provides software development services based on machine learning, reinforcement learning, and deep learning. To solve business problems, we use the following technologies, frameworks, and approaches:

Machine Learning

Machine Learning

Machine Learning is one of the branches of artificial intelligence. The basic principle is that machines receive data and “learn” from it. It is currently the most promising AI-powered business

Deep Learning

Deep Learning

Deep learning is a subset of machine learning. It uses machine learning techniques to solve business problems by applying neural networks to choose the best adaptation model in industrial enterprise

Edge AI

Edge computing consists of several methods that bring data collection, analysis, and processing to the network’s edge. It means that computing power and data storage is where the actual data

NVIDIA Jetson

The Jetson family of modules all use the same NVIDIA CUDA-X™ software and support cloud-native technologies like containerization and orchestration to build, deploy, and manage AI at the edge. With

FPGAs for Artificial Intelligence (AI)

With the growing popularity of using machine learning algorithms to extract and process information from raw data, there was a race between FPGA and GPU vendors to offer an HW

FPGA with Nvidia Jetson for AI solutions. Nvidia Jetson Nano, Jetson TX2, Jetson Xavier NX, Jetson AGX Xavier AI platforms in FPGA developing

FPGA with Nvidia Jetson

NVIDIA Jetson is the leading Edge AI computing platform used by over a million developers and companies worldwide. With cloud support across all NVIDIA Jetson products, intelligent machine makers and AI-powered embedded systems developers

FPGA Design Services

RISC-V (Rocket, VexRiscv, PicoRV), PCIe, SATA, NVMe, USB, GbE, 10G, 40G, Communication controllers, VGA, HDMI, DVI, Video controllers, GPIO, I2C, I3C, SPI, QSPI, TileLink, AXI, AXIS, Avalon, Wishbone

FPGA Design Services

SystemVerilog/Verilog/VHDL, C/C++, Chisel, SpinalHDL, MyHDL, TCL, CI/CD for FPGA projects, Vivado/System Generator/Vitis/Vivado HLS, Quartus/Intel HLS Compiler
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Our team is an expert in FPGA design. We maintain our service at a high level, which allows us to provide comprehensive solutions for FPGA design for various systems. Our company keeps pace with the times, has extensive experience in existing FPGA technologies. Using multiple technologies, practical and theoretical knowledge, experience in developing individual solutions for FPGA, we create a unique customer solution. If you need our expertise in developing or creating a unique FPGA solution, we will be happy to help you.

When implementing a project using FPGA technologies, the device’s budget, time, development complexity, performance requirements, and business logic are considered. ShuraCore team has deep industry expertise and high technical qualifications in FPGA solution development, which allows us to participate in various projects, not being limited to any one area of development. Below is our experience with multiple technologies for FPGA:

Compiler Design

Compiler Design Services

Github Linkedin Twitter Instagram Facebook ShuraCore specializes in implementing new and modern ports: GCC, GDB, GNU libraries, Binutils, LLDB, LLVM utilities, and libraries. We are

IP Cores

Intellectual Property (IP) Core is a block of logic or data used to create FPGA or particular purpose integrated circuit solutions. As a critical element

Our development team uses the following software processors in FPGA design: RISC-V (Rocket, VexRiscv, PicoRV), NIOS ||, Microblaze, etc.

Software Processors

When designing embedded systems, FPGA often requires some form of a controller in the system. This controller can be a simple microcontroller or a full-fledged

ShuraCore uses SystemVerilog/Verilog/VHDL, C/C++, Chisel, SpinalHDL, MyHDL, and TCL for FPGA Software Development. Programming Language.

Programming Languages

The programming language for FPGA is commonly referred to as hardware description language because it is used to describe or design hardware. For FPGA programming,

We use CI/CD for FPGA projects, Vivado/System Generator/Vitis/Vivado HLS, Quartus/Intel HLS Compiler, Matlab/Simulink.Tools.

Tools

Software development, like any other field of activity, requires specific tools. Our team of specialists uses proven tools that effectively develop and test software for FPGA, allowing

FPGA with Nvidia Jetson for AI solutions. Nvidia Jetson Nano, Jetson TX2, Jetson Xavier NX, Jetson AGX Xavier AI platforms in FPGA developing

FPGA with Nvidia Jetson

NVIDIA Jetson is the leading Edge AI computing platform used by over a million developers and companies worldwide. With cloud support across all NVIDIA Jetson products,

DevOps for FPGA

Our company uses advanced technologies DevOps for FPGA, which allow us to develop projects on time and optimize risks when designing FPGA. Improved deployment frequency

FPGA Verification

Verification is the verification of the device’s model being developed, designed by a team of specialists in one of the hardware description languages, based on

HLS for FPGA

High-Level Synthesis (HLS) is used to create digital devices using high-level languages. The main goal of HLS products is to simplify the FPGA design process for a

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