Artificial Intelligence at the Edge

Microchip

Microchip FPGA’s enabling Artificial Intelligence at the Edge

Artificial Intelligence and Machine Learning on the network’s edge require workload efficient computing at the lowest power and thermal headroom for operation in constrained environments.  For this application, mid-range density FPGAs are an excellent option for implementing designs. The challenge is how to deploy scalable and extensible neural networks, and how to enable software engineers with FPGA-based AI solutions performing efficient inferencing.

Microchip’s newest video and image processing solutions portfolio enabled by the PolarFire® FPGA Video and Imaging Kit. The new kit enables developers to implement Smart Embedded Vision systems with the lowest power and smallest form factor for edge applications leveraging artificial intelligence and high-resolution imaging. It also helps  developers get started with the RISC-V based PolarFire SoC, and MATLAB®/Simulink® on FPGA-in-the-Loop simulation. The PolarFire family continues to hit key milestones.

Smart Embedded Vision is opening up new possibilities for implementing systems that rely on visual data to make decisions across a broad spectrum of applications.  Machine vision, thermal imaging, video surveillance, robotics, machine learning inference on the edge and HMI all rely on cameras and displays that demand low power while supporting high-speed interfaces as well as security in data, and in design so that IP is protected. The inherent parallel processing and high-speed I/O capabilities of FPGAs makes them ideal processing platforms for delivering the high data throughputs needed for both high-resolution imaging and machine learning algorithms.

Microchip provides FPGA imaging and video solutions to enable the evaluation of multiple protocols and the development of a host of image and video processing applications. As a best-in-class imaging and video platform, Microchip’s solutions come with a complete ecosystem, including comprehensive application-specific hardware, optimized intellectual property suite for image processing, sample reference designs, demonstration designs and collateral. Compared to MCU, CPU, GPUs and AI ASICs, Microchip FPGAs:

  • Offer large DSP compute capacity (up to 1480 x18 x 18 Math Blocks) vs. MCU/ MPU/ CPU
  • Have lower power dissipation (~3-4W Core Power) vs. CPU/ GPU (>20W)
  • Have up to 50% lower power dissipation over competitive mid-density FPGAs
  • Offer scalability based on required performance
  • Integrate video, connectivity, security etc. vs. ASICs

 

Smart Embedded Vision (SEV) Kit

Our new PolarFire FPGA Video and Imaging Kit offers high-performance evaluation of 4K image processing and rendering using dual camera sensors as well as numerous display interfaces. Now featuring the PolarFire MPF300T production device, the kit is purpose-built for effortless prototyping of popular imaging and video protocols including MIPI CSI-2 TX, MIPI CSI-2 RX, HDMI 1.4 TX, HDMI2.0, DSI, and HD/3G SDI. The kit is part of our broader Smart Embedded Vision solutions for implementing systems that rely on visual data to make decisions across a broad spectrum of applications like drones, machine vision, thermal imaging, gaming, video surveillance, robotics, Advanced Driver Assistance Systems (ADAS), machine learning and Human-Machine Interfaces (HMIs).

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PolarFire FPGA's and Machine Learning

PolarFire FPGAs are ideal for mid-bandwidth (4K/2K) imaging/video and machine learning edge applications due to their rich memory, their Digital Signal Processor (DSP) resources and their low power consumption that is up to 50 percent lower than equivalent static random-access memory (SRAM)-based devices. With artificial intelligence (AI) increasingly being integrated into embedded vision systems, Our growing Smart Embedded Vision solutions portfolio includes our new PolarFire FPGA Video and Imaging Kit, imaging software and IP and machine learning inference IP. Microchip’s programmable hardware enables a power efficient imaging and video solution platform for embedded and edge computing applications.

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VectorBlox

Coming soon: Microchip’s VectorBlox Accelerator Software Development Kit and Neural Network IP for easily creating low-power FPGA Smart Embedded Vision Solutions.

The tool kit can execute models in TensorFlow and the open neural network exchange (ONNX) format which offers the widest framework interoperability. Unlike alternative FPGA solutions, Microchip’s VectorBlox Accelerator SDK is supported on Linux® and Windows® operating systems, and it also includes a bit accurate simulator which provides the user the opportunity to validate the accuracy of the hardware while in the software environment. The PolarFire FPGA neural network IP is available in a range of sizes to match the performance, power, and package size tradeoffs for the application, enabling customers to implement their solutions in package sizes as small as 11 × 11 mm.

General availability for Microchip’s VectorBlox Accelerator SDK Early access program starts in June 2020.


Hello FPGA

The Hello FPGA kit is a low cost, compact-sized, entry-level platform targeted towards end-users with low to medium FPGA knowledge. The kit supports powerful demos in Image Processing, Signal Processing, Artificial Intelligence, and can measure the live FPGA core power consumption while running designs. The kit also allows users to freeze the design while maintaining the i/o state for low power applications, using Flash Freeze mode.  The kit features Arduino & Mikrobus connectors for flexibility when it comes to prototyping, and expansion kits, allowing for easy adoption in future projects.

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SmartFusion2

SmartFusion2 SoC FPGAs Offer More Resources in Low-Density Devices with the Lowest Power, Proven Security, and Exceptional Reliability. SmartFusion2 SoC FPGAs offer 5K–150K LEs with a 166 MHz ARM Cortex-M3 processor, including ETM and instruction cache with on-chip eSRAM and eNVM, and a complete microcontroller subsystem with extensive peripherals, including CAN, TSE, and USB. These devices are also ideal for general purpose functions such as Gigabit Ethernet or dual PCI Express control planes, bridging functions, input/output (I/O) expansion and conversion, video/image processing, system management, and secure connectivity.

The Hello FPGA Kit, based on the SmartFusion ®2 FPGA with its Arm ® Cortex ®-M3 processor with embedded Flash to enable you to kickstart your FPGA journey. The kit simplifies FPGA evaluation, allowing you to experience the benefits of employing an FPGA in your design and accelerate prototype development.  

Buy now

Advanced driver assistance systems (ADAS) will be the driving force behind achieving Vision Zero, the multi-national project to reduce the number of fatalities and serious injuries caused by road traffic to zero. Microchip is enabling ADAS through its expertise in FPGA’s, Smart Embedded Vision, sensor connectivity and signal conditioning, high-speed data transfer, timing solutions and commitment to functional safety. As the level of autonomy progresses, the number of ADAS sensors in a car will increase from two or three to over 30, including forward/rear/side facing cameras, forward-looking radar and LiDAR. Microchip’s expertise in safety-critical connectivity will form the automotive superhighway for ADAS. We enable you to create secured, connected systems to detect any bumps in the road, with the speed and safety needed to support emerging ADAS applications.

Modern vehicles are the sum of tens of thousands of components, each one of which has to be designed with safety, security and reliability in mind.  The transport vehicle is becoming increasingly connected, both in-vehicle and to today’s rapidly expanding IoT world, enabling a smarter, greener, safer future.

Microsemi AI solution for ADAS is based on FPGAs, which provide core data acquisition, processing and display functions while providing industry’s best reliability and security in small footprint packages crucial for building differentiated, secure and reliable advanced driver assist systems. There is support for various communications interfaces for capturing data like Camera, Radar etc. These are available as hard or soft IPs. Customization of sensor interface as per design is supported. Microsemi FPGAs offer support for complex algorithms required for multi sensor input, image processing at high speeds. FPGAs offer crucial advantage over DSPs in providing parallel processing, enabling faster responses to potential hazards.

 

Hello FPGA

The Hello FPGA kit is a low cost, compact-sized, entry-level platform targeted towards end-users with low to medium FPGA knowledge. The kit supports powerful demos in Image Processing, Signal Processing, Artificial Intelligence, and can measure the live FPGA core power consumption while running designs. The kit also allows users to freeze the design while maintaining the i/o state for low power applications, using Flash Freeze mode.  The kit features Arduino & Mikrobus connectors for flexibility when it comes to prototyping, and expansion kits, allowing for easy adoption in future projects.

Buy now

 

 

PolarFire FPGA's and Machine Learning

PolarFire FPGAs are ideal for mid-bandwidth (4K/2K) imaging/video and machine learning edge applications due to their rich memory, their Digital Signal Processor (DSP) resources and their low power consumption that is up to 50 percent lower than equivalent static random-access memory (SRAM)-based devices. With artificial intelligence (AI) increasingly being integrated into embedded vision systems, Our growing Smart Embedded Vision solutions portfolio includes our new PolarFire FPGA Video and Imaging Kit, imaging software and IP and machine learning inference IP. Microchip’s programmable hardware enables a power efficient imaging and video solution platform for embedded and edge computing applications.

Learn more   


Smart Embedded Vision (SEV) Kit

Our new PolarFire FPGA Video and Imaging Kit offers high-performance evaluation of 4K image processing and rendering using dual camera sensors as well as numerous display interfaces. Now featuring the PolarFire MPF300T production device, the kit is purpose-built for effortless prototyping of popular imaging and video protocols including MIPI CSI-2 TX, MIPI CSI-2 RX, HDMI 1.4 TX, HDMI2.0, DSI, and HD/3G SDI. The kit is part of our broader Smart Embedded Vision solutions for implementing systems that rely on visual data to make decisions across a broad spectrum of applications like drones, machine vision, thermal imaging, gaming, video surveillance, robotics, Advanced Driver Assistance Systems (ADAS), machine learning and Human-Machine Interfaces (HMIs).

Buy now

VectorBlox

Coming soon: Microchip’s VectorBlox Accelerator Software Development Kit and Neural Network IP for easily creating low-power FPGA Smart Embedded Vision Solutions.

The tool kit can execute models in TensorFlow and the open neural network exchange (ONNX) format which offers the widest framework interoperability. Unlike alternative FPGA solutions, Microchip’s VectorBlox Accelerator SDK is supported on Linux® and Windows® operating systems, and it also includes a bit accurate simulator which provides the user the opportunity to validate the accuracy of the hardware while in the software environment. The PolarFire FPGA neural network IP is available in a range of sizes to match the performance, power, and package size tradeoffs for the application, enabling customers to implement their solutions in package sizes as small as 11 × 11 mm.

General availability for Microchip’s VectorBlox Accelerator SDK Early access program starts in June 2020.


SmartFusion2

SmartFusion2 SoC FPGAs Offer More Resources in Low-Density Devices with the Lowest Power, Proven Security, and Exceptional Reliability. SmartFusion2 SoC FPGAs offer 5K–150K LEs with a 166 MHz ARM Cortex-M3 processor, including ETM and instruction cache with on-chip eSRAM and eNVM, and a complete microcontroller subsystem with extensive peripherals, including CAN, TSE, and USB. These devices are also ideal for general purpose functions such as Gigabit Ethernet or dual PCI Express control planes, bridging functions, input/output (I/O) expansion and conversion, video/image processing, system management, and secure connectivity.

The Hello FPGA Kit, based on the SmartFusion ®2 FPGA with its Arm ® Cortex ®-M3 processor with embedded Flash to enable you to kickstart your FPGA journey. The kit simplifies FPGA evaluation, allowing you to experience the benefits of employing an FPGA in your design and accelerate prototype development.  

Buy now

 

PIC-IoT WG Development Board

The PIC-IoT WG Development Board combines a powerful PIC24FJ128GA705 MCU, an ATECC608A CryptoAuthentication™ secure element IC and the fully-certified ATWINC1510 Wi-Fi® network controller - which provides the most simple and effective way to connect your embedded application to the Google Cloud IoT Core. The board also includes an on-board debugger, and requires no external hardware to program and debug the MCU.

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SAM R34 Low Power LoRA Sub-GHz System-in-Package

Microchip has a LoRa® technology wireless solution to address increasing demands on end-devices for long range connectivity, low-power for battery operation, and low infrastructure cost for volume deployment. The SAM R34/R35 is a highly-integrated LoRa® System-in-Package (SiP) family which includes an ultra-low power, high-performance 32-bit microcontroller (MCU), LoRa transceiver and software stack. With certified reference designs, and proven interoperability with major LoRaWAN™ gateway and network providers, the SAM R34/35 SiPs significantly reduce time to market.

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AI at the Edge - Industrial

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AI at the Edge - Transportation

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