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Best $100-$300 FPGA development board in 2018?
Hello, I’ve been trying to decide on a FPGA development board, and have only been able to find posts and Reddit threads from 4-5 years ago. So I wanted to start a new thread and ask about the best “mid-range” FGPA development board in 2018. (Price range $100-$300.) I started with this Quora answer about FPGA boards, from 2013. The Altera DE1 sounded good. Then I looked through the Terasic DE boards. Then I found this Reddit thread from 2014, asking about the DE1-SoC vs the Cyclone V GX Starter Kit: https://www.reddit.com/FPGA/comments/1xsk6w/cyclone_v_gx_starter_kit_vs_de1soc_board/ (I was also leaning towards the DE1-SoC.) Anyway, I thought I better ask here, because there are probably some new things to be aware of in 2018. I’m completely new to FPGAs and VHDL, but I have experience with electronics/microcontrollers/programming. My goal is to start with some basic soft-core processors. I want to get some C / Rust programs compiling and running on my own CPU designs. I also want to play around with different instruction sets, and maybe start experimenting with asynchronous circuits (e.g. clock-less CPUs) Also I don’t know if this is possible, but I’d like to experiment with ternary computing, or work with analog signals instead of purely digital logic. EDIT: I just realized that you would call those FPAAs, i.e. “analog” instead of “gate”. Would be cool if there was a dev board that also had an FPAA, but no problem if not. EDIT 2: I also realized why "analog signals on an FPGA" doesn't make any sense, because of how LUTs work. They emulate boolean logic with a lookup table, and the table can only store 0s and 1s. So there's no way to emulate a transistor in an intermediate state. I'll just have play around with some transistors on a breadboard. UPDATE: I've put together a table with some of the best options:
A very simple FPGA development board that plugs into a Raspberry Pi, so you have a "backup" hard-core CPU that can control networking, etc. Supports a huge range of pmod accessories. You can write a program/circuit so that the Raspberry Pi CPU and the FPGA work together, similar to a SoC. Proprietary bitstream is fully reverse engineered and supported by Project IceStorm, and there is an open-source toolchain that can compile your hardware design to bitstream. Has everything you need to start experimenting with FPGAs.
Xilinx Zynq 7-Series SoC - ARM Cortex-A9 processor, and Artix-7 FPGA. 125 IO pins. 1GB DDR2 RAM. Texas Instruments WiLink 8 wireless module for 802.11n Wi-Fi and Bluetooth 4.1. No LEDs or buttons, but easy to wire up your own on a breadboard. If you want to use a baseboard, you'll need a snickerdoodle black ($195) with the pins in the "down" orientation. (E.g. The "breakyBreaky breakout board" ($49) or piSmasher SBC ($195)). The snickerdoodle one only comes with pins in the "up" orientation and doesn't support any baseboards. But you can still plug the jumpers into the pins and wire up things on a breadboard.
Has one of the latest Xilinx SoCs. 2 GB (512M x32) LPDDR4 Memory. Wi-Fi / Bluetooth. Mini DisplayPort. 1x USB 3.0 type Micro-B, 2x USB 3.0 Type A. Audio I/O. Four user-controllable LEDs. No buttons and limited LEDs, but easy to wire up your own on a breadboard
Xilinx Zynq 7000 SoC (ARM Cortex-A9, 7-series FPGA.) 1 GB DDR3 RAM. A few switches, push buttons, and LEDs. USB and Ethernet. Audio in/out ports. HDMI source + sink with CEC. 8 Total Processor I/O, 40 Total FPGA I/O. Also a faster version for $299 (Zybo Z7-20).
Same as DE10-Standard, but not as many peripherals, buttons, LEDs, etc.
icoBoard ($100). (Buy it here.) The icoBoard plugs into a Raspberry Pi, so it's similar to having a SoC. The iCE40-HX8K chip comes with 7,680 LUTs (logic elements.) This means that after you learn the basics and create some simple circuits, you'll also have enough logic elements to run the VexRiscv soft-core CPU (the lightweight Murax SoC.) The icoBoard also supports a huge range of pluggable pmod accessories:
numato Mimas A7 ($149). An excellent development board with a Xilinx Artix 7 FPGA, so you can play with a bigger / faster FPGA and run a full RISC-V soft-core with all the options enabled, and a much higher clock speed. (The iCE40 FPGAs are a bit slow and small.)
I ordered a iCE40-HX8K Breakout Board to try out the IceStorm open source tooling. (I would have ordered an icoBoard if I had found it earlier.) I also bought a numato Mimas A7 so that I could experiment with the Artix 7 FPGA and Xilinx software (Vivado Design Suite.)
What can I do with an FPGA? / How many LUTs do I need?
VexRiscv is "A FPGA friendly 32 bit RISC-V CPU implementation." This is a RISC-V implementation written in SpinalHDL. VexRiscv has a lot of plugin and configuration options. The Murax SoC is a very light SoC that can run on an iCE40-HX8k (but probably not the 1k FPGA that only has 1,280 LUTs). The Briey SoC only runs on Xilinx or Altera FPGAs.
There's a pretty interesting debate in the AI space right now on whether FPGAs or ASICs are the way to go for hardware-accelerated AI in production. To summarize, it's more about how to operationalize AI - how to use already trained models with millions of parameters to get real-time predictions, like in video analysis or complex time series models based on deep neural networks. Training those AI models still seems to favor GPUs for now. Google seem to be betting big on ASICs with their TPU. On the other hand, Microsoft and Amazon seem to favor FPGAs. In fact Microsoft have recently partnered with Xilinx to add FPGA co-processors on half of their servers (they were previously only using Intel's Altera). The FPGA is the more flexible piece of hardware but it is less efficient than an ASIC, and have been notoriously hard to program against (though things are improving). There's also a nice article out there summarizing the classical FPGA conundrum: they're great for designing and prototyping but as soon as your architecture stabilizes and you're looking to ramp up production, taking the time to do an ASIC will more often be the better investment. So the question (for me) is where AI inference will be in that regard. I'm sure Google's projects are large scale enough that an ASIC makes sense, but not everyone is Google. And there is so much research being done in the AI space right now and everyone's putting out so many promising new ideas that being more flexible might carry an advantage. Google have already put out three versions of their TPUs in the space of two years Which brings me back to Xilinx. They have a promising platform for AI acceleration both in the datacenter and embedded devices which was launched two months ago. If it catches on it's gonna give them a nice boost for the next couple of years. If it doesn't, they still have traditional Industrial, Aerospace & Defense workloads to fall back on... Another wrinkle is their SoCs are being used in crypto mining ASICs like Antminer, so you never know how that demand is gonna go. As the value of BTC continues to sink there is constant demand for more efficient mining hardware, and I do think cryptocurrencies are here to stay. While NVDA has fallen off a cliff recently due to excess GPU inventory, XLNX has kept steady. XLNX TTM P/E is 28.98 Semiconductors - Programmable Logic industry's TTM P/E is 26.48 Thoughts?
Browse other questions tagged mining-pools mining-hardware fpga or ask your own question. The Overflow Blog How to communicate more deliberately and efficiently when working remotely See also: Non-specialized hardware comparison Below are statistics about the Bitcoin Mining performance of ASIC hardware and only includes specialized equipment that has been shipped.. GPUs, CPUs and other hardware not specifically designed for Bitcoin mining can be found in the Non-specialized_hardware_comparison.. Notes: Altera. The compile the code on an different Altera device then DE2-115, you need to set the Device to be the correct one. Find the correct fpga package number and add it, for the DE0-Nano this is EP4CE22F17C6. Be sure to select the correct one, because the hardware effects the location of your pins, which you will need in the clock pin step. Round 2011 some miners began switching from GPUs to FPGAs, (Discipline Programmable Gate Arrays), after the primary implementation of Bitcoin mining came out in Verilog, (a hardware design language that's used to program FPGAs). Hardware startup Agilemine has developed the UltraMiner FPGA cryptocurrency mining board, which they claim has double the speed and 4 times the energy efficiency over ... Mining im Selbstversuch: Von der Idee bis zur Überweisung. Hinweis: Der Artikel Mining mit Gaming-GPUs: Aktuelle Benchmarks für Ethereum, Monero und Zcash enthält mittlerweile aktuellere ...
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