$5 Tang Nano FPGA Board Features GOWIN GW1N “LittleBee” FPGA

Last year, we wrote about Lichee Tang FPGA board powered by Anlogic EG4S20 FPGA and targeting RISC-V development for just under $15. The company, now called Sipeed, has made an even cheaper FPGA board with Tang Nano equipped with GOWIN Semi GW1N FPGA part of the company’s LittleBee family. Sipeed Tang Nano Sipeed Tang Nano specifications: FPGA – Gowin GW1N-1-LV FPGA with 1,152 LUT4, 864 Flip-Flops(FF), 72Kbit Block SRAM, 4x B-SRAM, 96Kbit user flash, 1x PLL, 4x I/O banks System Memory – 64Mbit (8MB) 3.3V PSRAM Display – Standard 40-pin RGB LCD interface with on-board screen backlight driver circuit (default normally open, EN pin can be connected to FPGA) USB – USB Type-C port for download and power supply Expansion – 34 I/O ports and power pins on headers (unpopulated), breadboard-compatible Misc – RGB LED, 2x user buttons, 24MHz crystal oscillator Power Supply – 5V via USB-C port (at least […]

Pixblasters MS1 Video LED Controller Outputs HDMI Input to 16K+ LED Video Walls (Crowdfunding)

Pixblaster Video LED Controller Pixblasters, a company focused on LED signage and video display, have started a Crowd Supply campaign for their MS1 Video Controller. The Pixblaster MS1 controller can be attached to any laptop or computer with HDMI output (think Raspberry Pi SBC) and control 16,384 LEDs without any programming, physical modifications or soldering. Extreme Scalability The market the MS1 video controller is aimed at is small business and makers, who hadn’t before had a controller with this much scalability.  The company is saying that the MS1 can be daisy-chained together to control hundreds of thousands of LEDs and act as a full video monitor across hundreds of meters of LED strips. Programming The unit can easily and with little technical knowledge connect WS212B-Based addressable LED strips together for a complex output of digital displays, even mirroring a video display in some instances. Target Users The ability to use […]

Spartan Edge Accelerator Arduino Compatible Board Combines ESP32 & Spartan-7 FPGA

Spartan Edge Accelerator

Xilinx Spartan FPGAs have been around for a while, and a few years ago we covered Spartan-6 FPGA boards such as Spartixed and miniSpartan6+.  Seeed Studio has now launched another Xilinx Spartan board with WiFi and Bluetooth connectivity. Spartan Edge Accelerator Board follows Arduino UNO form factor and combines a more recent Xilinx Spartan-7 FPGA with Espressif Systems ESP32 WiFi + Bluetooth chip. Spartan Edge Accelerator specifications:  FPGA – Xilinx Spartan-7 XC7S15 FPGA with 12.8K Logic Cells and 360Kb block RAM WiSoC – Espressif Systems ESP32 SoC with 802.11 b/g/n 2.4GHz WiFi and Bluetooth 4.1  BLE Storage – SPI flash, MicroSD card slot Video Output – Mini HDMI Video Input – CSI Camera Interface with support for OV5640 sensor USB – USB type-C port Expansion Arduino UNO headers (5V) FPGA I/O header DAC output and ADC input header (via 8-bit ADC1173 chip) 2x Grove connectors (I2C and digital I/O) Debugging […]

ULX3S Education Board is Powered by Lattice Semi ECP5 FPGA & ESP32 WiFi/BLE Module

ULX3S Lattice ECP5 FPGA Educational Board

A few days ago, we covered the KiCAD designed OrangeCrab open-source hardware board powered by a Lattice Semi ECP5 FPGA, and compliant with Adafruit Feather form factor. It’s turned out there’s another Lattice Semi ECP5 FPGA board that’s also designed with KiCAD and open source hardware. Radiona ULX3S differs are it’s larger and exposes more I/Os since it was specifically designed to meet the meets of the digital logic course at the Faculty of Electrical Engineering and Computing (FER) of the University of Zagreb in Croatia. ULX3S specifications: FPGA – Lattice ECP5 LFE5U-85F-6BG381C with 84K LUT System Memory – 32MB SDRAM @ 166 MHz Storage – 4–16MB Quad-SPI Flash for FPGA config and user data storage; MicroSD slot Audio – 3.5 mm jack with 4 contacts (analog stereo + digital audio or composite video) Video – Digital video (GPDI General-Purpose Diferential Interface) with 3.3V-5V I2C bidirectional level shifter Display – […]

OrangeCrab is an Open Source Hardware, Feather-Compatible Lattice ECP5 FPGA Board

Lattice ECP5 Feather board

Lattice ECP5 FPGA powered OrangeCrab is the work of Greg Davill who designed the Adafruit Feather-compatible board in KiCAD, crowdsourced schematics/PCB checking and published his progress on Twitter, and published the files  of the open source hardware board on Github. OrangeCrab board hardware specifications: FPGA – Lattice ECP5 25/45/85 variants System Memory – Up  to 8Gbit DDR3 Memory (x16) Storage – 128Mbit QSPI FLASH Memory (Bitstream + User storage), 4-bit MicroSD socket USB – Micro USB connector, full-speed direct USB connection to FPGA Programming – 10-pin FPGA programming header Expansion – I/O’s broken out via 30 through holes: GPIO, SPI, I2C, Analog, … 7x diff pairs, 1x single ended only Misc – Reset Button, charge LED (Green:  external power, Yellow: when charging, No color: when running off battery), 48MHz Oscillator Power Supply – 5V via USB port, battery header for LiPo battery + battery charger chip Dimensions – Adafruit Feather […]

Intel Agilex SoC FPGA Features Four Arm Cortex-A53 Cores

Intel Agilex SoC FPGA

Intel announced their new Agilex FPGA family manufactured with a  10nm process earlier this April, but it only caught my eyes recently when I saw “Agilex SoC FPGA” listed in Linux 5.2 Arm’s changelog. The Intel SoC FPGA is there simply because it comes with four Arm Cortex-A53 cores. Three family have been announced so far, although the later is shown as coming soon: Intel Agilex F-Series FPGAs and SoCs – Transceiver support up to 58 Gbps, increased DSP capabilities, high system integration, and 2nd Gen Intel Hyperflex architecture for a wide range of applications in Data Center, Networking, and Edge. Option to integrate the quad-core Arm Cortex-A53 processor. Intel Agilex I-Series SoC FPGAs – Optimized for high performance processor interface and bandwidth intensive applications. Coherent attach to Intel Xeon processors with Compute Express Link, hardened PCIe Gen 5 support and transceiver support up to 112 Gbps. Intel Agilex M-Series […]

MYIR Announces Xilinx Zynq UltraScale+ MPSoC SoM and Development Board

MYD-CZU3EG development board

MYIR Technology has been selling Xilinx Zynq-7000 FPGA + Arm systems-on-module since 2016, but the Chinese company has now announced new modules based on the more powerful Xilinx Zynq Ultrascale+ MPSoC with Arm Cortex-A53 cores, Arm Cortex-R5 cores, and Ultrascale FPGA fabric, as well as a corresponding development board. MYC-CZU3EG Zynq UltraScale+ MPSoC CPU Module CPU module specifications: MPSoC – Xilinx Zynq UltraScale+ XCZU3EG-1SFVC784E (ZU3EG, 784 Pin Package) MPSoC with quad-core Arm Cortex-A53 processor @ 1.2 GHz, dual-core Cortex-R5 processor @ 600 MHz, Arm Mali-400MP2 GPU, and 16nm FinFET+ FPGA fabric (154K logic cells, 7.6 Mb memory, 728 DSP slices) System Memory – 4GB DDR4 @ 2,400MHz Storage – 4GB eMMC Flash, 128MB QSPI Flash On-module chips Gigabit Ethernet PHY USB PHY Intel Power Module Clock Generator 2x Samtec 0.5mm pitch 160-pin high-speed headers bringing out Networking – Gigabit Ethernet USB – USB 2.0 interface 4x PS GTR transceivers along with […]

Arm Techcon 2019 Schedule – Machine Learning, Security, Containers, and More

Arm Techcon 2019

Arm TechCon will take place on October 8-10, 2019 at San Jose Convention Center to showcase new solutions from Arm and third-parties, and the company has now published the agenda/schedule for the event. There are many sessions and even if you’re not going to happen it’s always useful to checkout what will be discussed to learn more about what’s going on currently and what will be the focus in the near future for Arm development. Several sessions normally occur at the same time, so as usual I’ll make my own virtual schedule with the ones I find most relevant. Tuesday, October 8  09:00 – 09:50 – Open Source ML is rapidly advancing. How can you benefit? by Markus Levy, Director of AI and Machine Learning Technologies, NXP Over the last two years and still continuing, machine learning applications have benefited tremendously from the growing number of open source frameworks, tools, […]

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