AI & FPGA
FPGA for Artificial Intelligence
AI-related technologies are showing robust growth. At the same time, smart AI algorithms are becoming more and more complex. In the past, the graphics processing units (GPU) were able to accelerate numerous forms of workloads in artificial intelligence and machine learning applications. Today, they are not enough. GPUs consume too much power which is expensive and inefficient. That is where FPGA programming comes to the rescue. Being flexible and easily reconfigurable, they outperform traditional GPUs and CPUs.
FPGAs show great potential for AI applications with changing requirements. Unlike traditional processors, they include multiple kinds of resources that can be freely adapted for modified environments. FPGA provides flexibility, continuous parallel computing, and comparatively high performance/consumption balance.
Advantages of FPGAs in AI
FPGA allows building unique AI solutions with an easy adaptation to changes. At the same time, it does not waste processing time fetching instructions and data, as it is defined by hardware.
FPGAs are designed to perform many operations in parallel, which makes them ideal for managing large networks and boosting the overall performance.
The programmable architecture allows adding an almost unlimited amount of FPGAs per slot in case the AI algorithm is more in size than a single FPGA can handle.
FPGAs provide excellent performance using less power than, hence, GPUs. Besides, they are resilient and can operate in harsh conditions for extended periods of time.
Large amounts of data can be processed in real-time due to lots of fast, on-chip local memory.
Minimal access time
Large amounts of data are processed very fast due to the high memory bandwidth.
Application cases of FPGA-based AI solutions
Image transcoding & broadcasting
Real-time UHD video processing, AI-based categorisation of TV shows on DTV platforms, audio over IP for sound reinforcement in professional audio systems, augmented and virtual reality, real-time digital character PoC.
FPGA-based automotive solutions
in-vehicle infotainment (IVI), advanced driver-assistance systems (ADAS), automated driving (AD), driver information systems, motor control algorithms, and other fault-tolerant solutions according to ISO-26262.
Next-gen test & measurement solutions
test & measurement platforms and real-time instrumentation, high-end consumer electronics with immersive displays, intelligent transport, and embedded real-time analytics.
intelligent vision-guided robotics, high-precision motor control algorithms, data center acceleration, smart grid, smart factory, IoT gateways and appliances, human machine interface, on-board electronics for trains and railways, 3D printing.
Smart solutions for medtech
genome research, hardware acceleration and data processing in molecular breeding and pharmacy, medical imaging with ultrasound, robot-assisted surgery, multi-parameter patient monitors & ECGs, diagnostics and clinical equipment.
Custom design services
real-time rendering, FPGA-based AI-enhanced video processing, automatic image recognition and classification, image stitching, embedded vision systems, face detection & tracking, hand gesture detection, speed sign detection, object counting, smart home.
Our projects in FPGA design
Our technology map in FPGA
Xilinx Vitis AI, Xilinx Vivado Design Suite, Intel Quartus Prime
Xilinx Deep Neural Network (xDNN), Xilinx Alveo, Intel OpenVINO Toolkit, TensorFlow, Keras, Caffe
Tools & Languages
C++, Python, Matlab/Simulink, Verilog, VHDL, HLS
High-speed interfaces, DDR4, JESD204b, SI, PI, Thermo modeling
In case you are looking for a team of professionals to support your FPGA board design or traditional approach for IP-core development in Verilog/VHDL, explore our FPGA services.
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