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Processor Development Tools | Embedded Processor

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BBONE-AI, Beagleboard.org

BeagleBone AI Development kits are most commonly a set of software tools which enables it's users the creation for a certain software package, software framework, hardware platform, computer system, video game console, operating system, or similar development platforms. BeagleBoard.org presents this innovative BeagleBone AI which has been designed to fill the gap between small SBCs (Single Board Computers) and more powerful SoC (System on Chip), with the added functionality of the BeagleBone Black header and mechanical compatibility. This development kit gives it's customers the opportunity to easily explore the expanding field which is artificial intelligence. The BeagleBone AI allows it's users to discover how AI can be used in everyday life via it's TI C66x DSP cores (digital-signal-processor) and EVE cores (embedded-vision-engine). Built on the already proven and reliable BeagleBoard.org this, open-source, Linux-based computer board is ideal for electronics engineers and hobbyists. Key Board Features BeagleBone Black mechanical and header compatibility. USB Type-C for power and superspeed dual-role controller; and USB Type-A host. Micro HDMI. Zero-download out-of-box software experience with Debian GNU/Linux. Gigabit Ethernet, 2.4/5GHz WiFi, and Bluetooth. Board Dimensions: 89 mm x 54 mm x 15 mm The Processor The BeagleBone AI uses a uniquely designed AM5729 Sitara processor which helps carry out multiple tasks for increased device usability. The processor includes various cores that work in tandem to complete an impressive product: Dual 1.5GHz ARM Cortex-A15 with out-of-order speculative issue 3-way superscalar execution pipeline for the fastest execution of existing 32-bit code. 2x C66 Floating-Point VLIW DSP supported by OpenCL. 4x Embedded Vision Engines (EVEs) supported by TIDL machine learning library. 2x Dual-Core Programmable Real-Time Un...

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RTK9763U02S01000BE, Renesas Electronics

The Renesas Evaluation board Kit for RZ/A3UL MPU QSPI Edition and consists of a module board (SOM) and a carrier board. Cortex-A55 Single ,RTOS-based high performance MPU running at 1GHz frequency on 64bit CPU, types of evaluation boards -QSPI version: QSPI Serial Flash (Boot) + DDR4

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CXD5602PWBEXT1E, Sony

SPRESENSE™ is a low-power board computer for the IoT that is equipped with a GPS receiver and supports High-Resolution Audio codecs. The board allows for IoT versatility and can be developed for a vast range of uses, such as a drone utilizing the GPS and high-performance processor, a smart speaker utilizing High-Resolution Audio recording and playback as well as the built-in full-digital amplifier, or a low-power time-lapse camera utilizing the camera interface. SPRESENSE™ will make the IoT smarter and more efficient. High-precision Positioning Features Ultra-low power consumption Multiple GNSS systems supported: GPS, GLONASS, SBAS, Galileo, and Beidu Advanced High-Resolution Audio features 192 kHz/24 bit High-Resolution Audio codec 192 kHz A/D converter 8 channel microphone inputs (for digital microphones) Full digital amplifier with BTL stereo output Extensive computing power Hexa-core ARM® Cortex®-M4F

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101-1270, Rabbit Semiconductor

BL4S200 Single-Board Computer Uses Rabbit® 4000 and Rabbit® 5000 Microprocessors Choice of Wi-Fi, ZigBee enabled, or Ethernet connectivity Friction lock connectors RabbitNet Compatible 40 digital I/O Up to 5 serial ports Battery-backed real-time clock Watchdog supervisor 8 analog input channels and 2 analog output channels BL4S200 Tool Kit Dynamic C CD-ROM, with complete product documentation on disk Printed getting started manual and Rabbit 4000 / 5000 Posters Demonstration Board with pushbutton switches and LEDs to demonstrate the I/O and TCP/IP capabilities of the BL4S200 USB programming cable, used to connect the BLS4200 to your PC USB port Universal AC adapter, 12Vdc 1A Rabbit

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New items

NCSM2450.DK1, Intel

Movidius Neural Compute Stick The Neural Network Compute Stick from Movidius™ allows Deep Neural Network development without the need for expensive, power-hungry supercomputer hardware. Simply prototype and tune the Deep Neural Network with the 100Gflops of computing power provided by the Movidius stick. A Cloud connection is not required. The USB stick form-factor makes for easy connection to a host PC while the on-board Myriad-2 Vision Processing Unit (VPU) delivers the necessary computational performance. The Myriad-2 achieves high-efficiency parallel processing courtesy of its twelve Very Long Instruction Word (VLIW) processors. The decision on parallel scheduling is carried out at program compile time, relieving the processors of this chore at run-time. Features Movidius 600MHz Myriad-2 SoC with 12 x 128-bit VLIW SHAVE vector processors 2MB of 400Gbps transfer-rate on-chip memory Supports FP16, FP32 and integer operations with 8-, 16- and 32-bit accuracy All data and power provided over a single USB 3.0 port on a host PC Real-time, on-device inference without Cloud connectivity Quickly deploy existing CNN models or uniquely trained networks Multiple Movidius Sticks can be networked to the host PC via a suitable hub Dimensions: 72.5 x 27 x 14mm Compile Automatically convert a trained Caffe -based Convolutional Neural Network (CNN) into an embedded neural network optimized for the on-board Myriad-2 VPU. The SDK also supports TensorFlow . Tune Layer-by-layer performance metrics for both industry-standard and custom-designed neural networks enable effective tuning for optimal real-world performance at ultra-low power. Validation scripts allow developers to compare the accuracy of...

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410-383-3EG, Digilent

The Digilent Genesys ZU is a stand-alone Zynq UltraScale+ MPSoC prototyping and development board. It is an advanced computing platform with powerful multimedia and network connectivity interfaces. The excellent mix of on-board peripherals, upgrade-friendly DDR4, Mini PCIe and microSD slots, multi-camera and high-speed expansion connectors are bound to support a wide number of use-cases. Upgraded memory interface The bundled microSD card includes an out-of-box demo that boots a Linux image built in petalinux and includes some test scripts for some of the peripherals

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RTK9RZN2L0S00000BE, Renesas Electronics

The Renesas Starter Kit for RZ/N2L is for evaluation or development using the RZ/N2L MPU With Emulator circuit is mounted, and program debugging can be started by simply connecting USB cable to PC (two USB cables are included, one for emulator and the other for power supply). Generic interfaces - Pmod /Grove /Qwiic /mikroBUS Rich functional ICs such as Gigabit Ethernet PHY and Octal Flash are mounted On-board RZ/N2L MPU 225-pin

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New items

KITA2GTC3995VTRBSTOBO1, Infineon

The Infineon evaluation board can start to develop, evaluate and test software. The TC399XE is mounted on a socket so that it can be easily changed, making it particularly suitable for early project development. Burst flash up to 4MBytes Asynchronous SRAM up to 2MByte Synchronous SRAM up to 4MByte High speed CAN transceivers

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New items

KITA2GTC3775VTRBSTOBO1, Infineon

The Infineon evaluation board can start to develop, evaluate and test software. The TC377TE evaluation device is mounted on a socket so that it can be easily changed, making it particularly suitable for early project development. High speed CAN transceivers LIN Transceiver Crystal 20MHz or external clock 8-DIP switches for configuration

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New items

102991187, Seeed Studio

The Seed Studio Grove AI HATis built around Speed MAix M1 AI MODULE for Edge computing. It has a Kendryte K210 processor inside. The Speed MAix M1 is a powerful RISC-V 600MHz AI module. It features a dual-core 64-bit CPU, 230GMULps 16-bit KPU(Neural Network Processor), FPU(Float Point Unit) supports DP&SP, and APU(Audio Processor) supports 8 mics. The Grove AI HAT for Edge computing board provides a variety of peripherals like I2C,UART,SPI,I2S,PWM and GPIO. Low cost Powerful Offers a LCD and a camera interface

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New items

410-346-20, Digilent

Arty Z7 Zynq-7000 Development Board The Arty Z7-20 is a development platform designed around the Xilinx Zynq-7000™ All Programmable System-on-Chip (AP SoC). The Zynq-7000 architecture integrates a dual-core, 650MHz ARM Cortex-A9 processor with Artix-7 series FPGA logic. This pairing surrounds a powerful processor with a unique set of software defined peripherals and controllers. The Vivado, Petalinux, and SDSoC toolsets each provide a path between defining your custom peripheral set and bringing its functionality up to a Linux OS or 'bare-metal' program running on the processor. Xilinx Zynq-7000 (XC7Z020-1CLG400C) Processor: 650MHz dual ARM Cortex-A9 core Look-up Tables (LUTs): 53200 Flip-flops: 106400 Block RAM: 630KB Clock Management Tiles: 4 Available Shield I/O: 49 DDR3 memory controller with 8 x DMA channels and 4 x AXI3 Slave ports High-bandwidth peripheral controllers: 1G Ethernet, USB 2.0, SDIO Low-bandwidth peripheral controller: SPI, UART, CAN, I²C Programmable from JTAG, Quad-SPI Flash or microSD card Programmable logic equivalent to Artix-7 FPGA Memory Board Memory and Power On-board IS43TR16256A-125KBL 512MB DDR3 SDRAM with 16-bit bus @ 1050Mbps On-board S25FL128S 16MB Quad-SPI Flash with 48-bit unique EUI-48/64™ compatible identifier microSD card slot Powered from USB or +7V to +15Vdc via barrel jack System Connectivity 10/100/1000 Ethernet via RJ45 connector USB-UART Bridge via micro-B socket USB-JTAG Programming via micro-B socket USB OTG PHY (supports Host only) via USB-A socket Audio and Video HDMI sink port (input) HDMI source port (output) PWM driven mono audio output via 3.5mm jack socket Switches and LEDs Reset and Program pushbuttons 4 x User pushbuttons 2 x User slide-switches 4 x User LEDs 2 x User...

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New items

CYTVII-B-E-1M-SK, Infineon

The Infineon evaluation board is a low cost easy to use evaluation board based on the traveo II body entry family of devices. It is designed in an Arduino form factor so that users can connect many off-the-shelf Arduino shields to it, to expand its functionality. High speed CAN transceiver USB to UART bridge User switch and user LED and potentiometer

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