Custom RISC-V Processor Built In VHDL

While ARM continues to make inroads into the personal computing market against traditional chip makers like Intel and AMD, it’s not a perfect architecture and does have some disadvantages. While it’s a great step on the road to software and hardware freedom, it’s not completely free as it requires a license to build. There is one completely open-source and free architecture though, known as RISC-V, and its design and philosophy allow anyone to build and experiment with it, like this build which implements a RISC-V processor in VHDL.

Since the processor is built in VHDL, a language which allows the design and simulation of integrated circuits, it is possible to download the code for the processor and then program it into virtually any FPGA. The processor itself, called NEORV32, is designed as a system-on-chip complete with GPIO capabilities and of course the full RISC-V processor implementation. The project’s creator, [Stephan], also struggled when first learning about RISC-V so he went to great lengths to make sure that this project is fully documented, easy to set up, and that it would work out-of-the-box.

Of course, since it’s completely open-source and requires no pesky licensing agreements like an ARM platform might, it is capable of being easily modified or augmented in any way that one might need. All of the code and documentation is available on the project’s GitHub page. This is the real benefit of fully open-source hardware (or software) which we can all get behind, even if there are still limited options available for RISC-V personal computers for the time being.

How does this compare to VexRISC or PicoSOC? We don’t know yet, but we’re always psyched to have choices.

Slice Your Next FPGA Design

A recent trend has been to convert high-level constructs into FPGA code like Verilog or VHDL. Silice goes the other way: it converts very hardware-specific concepts to Verilog and aims to be a more expressive and easier to use language.

Why Silice? The project’s web page enumerates its design goals:

  • A clean, simple syntax that clearly exposes the flow of operations and where clock cycles are spent.
  • Precise rules regarding flow control (loops, calls) and their clock cycle consumption.
  • Familiar hardware constructs such as always blocks, instantiation, expression tracking (wires).
  • An optional flow-control oriented design style (automatic FSM generation), that naturally integrates within a design: while, break, subroutines.
  • The possibility to easily describe pipelines.
  • Automatically takes care of creating flip-flops for variables, with automatic pruning (e.g. const or bindings).
  • Generic interfaces and grouped IOs for easy reuse and modular designs.
  • Generic circuits that can be instantiated and reused easily.
  • Explicit clock domains and reset signals.
  • Familiar syntax with both C and Verilog inspired elements.
  • Inter-operates with Verilog, allowing to import and reuse existing modules.
  • Powerful LUA-based pre-processor.

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FIR Filters For Xilinx

Digital filters are always an interesting topic, and they are especially attractive with FPGAs. [Pabolo] has been working with them in a series of blog posts. The latest covers an 8th order FIR filter in Verilog.  He covers some math, which you can find in many places, but he also shows how an implementation maps to DSP slices in a device. Then to reduce the number of slices, he illustrates folding which trades delay time for slice usage.

Folding takes a multi-stage parallel multiplication and breaks it into fewer multiplications done over a longer period of time. This reuses slices to reduce the number required for high-order filters.

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Using Docker To Sail Through Open-Source Xilinx FPGA Development

Until a few years ago, developing for FPGAs required the use of proprietary locked-down tools, but in the last few years, the closed-source dam has burst, and open-source FPGA tools such as Yosys, SimbiFlow, and Icestorm have come flooding out. Setting up a build environment for these exciting new tools can still be quite a challenge, but [Carlos Eduardo] has decided to make setting up an open-source toolchain for Xilinx FPGAs a breeze with Docker.

His image only has three prerequisites: Docker, Python 3, and OpenOCD (which is used to load your FPGA with your bespoke bitfile). After the Docker image has been built and all of the tools installed, [Carlos] guides you through using Python, FuseSoc, and SymbiFlow to build your first open-source Xilinx FPGA project.

In addition to making setup a whole lot easier, utilizing containers allows the same development environment to be built on Linux, Mac, and Windows (using WSL), which will make life a lot easier for teams working across different OSs.  [Carlos’s] Dockerfile is unique because it supports the popular Artix-7 series of FPGAs — for the Lattice FPGAs that have been supported for a lot longer, there are existing Docker files already up on DockerHub. It’s easier than installing the vendor’s toolchain!

If this has you thinking it might be time to dip your toes into open-source FPGA development, check out this rundown of open-source FPGA tools from the 2019 Superconference.

Arduino And FPGA Done Differently

FPGA guru [Max Maxfield] recently took a look at the XLR8 (pronounced accelerate) board from a company called Alorium. On the surface, it looks like another Arduino UNO clone. But instead of a CPU, it contains an Intel MAX10 FPGA that runs a softcore AVR processor. Of course, that’s only part of the story. If the board was just a mock Arduino using an FPGA, that’s not very interesting for practical purposes. However, by incorporating accelerator blocks or XBs, you can add FPGA modules to the soft CPU. [Max] shows an example that you can see in the video below where an FPGA block controls servos more easily than a standard Arduino. There’s also a version that looks like an Arduino Nano, but can clock much faster as well as use the XBs.

In addition to prebuilt XBs, there is a workflow to build your own if you are familiar with working with FPGAs. The products aren’t exactly new, but we enjoyed [Max’s] take on the product. We also appreciated the simple code examples showing exactly how you would convert a program to use the accelerated functions. Continue reading “Arduino And FPGA Done Differently”

Surf’s Up, A Styrofoam Ball Rides The Waves To Create A Volumetric Display

We are big fans of POV displays, particularly ones that move into 3D. To do so, they need to move even faster than their 2D cousins. [danfoisy] built a volumetric display that doesn’t move LEDs or any other digital display through space, or project light onto a moving surface. All that moves here is a bead of styrofoam and does so at up to 1 meter per second. Having low mass certainly helps when trying to hit the brakes, but we’re getting ahead of ourselves.

danfoisy vdatp 3d simulation

[danfoisy] and son built an acoustic levitator kit from [PhysicsGirl] which inspired the youngster’s science fair project on sound. See the video by [PhysicsGirl] for an explanation of levitation in a standing wave. [danfoisy] happened upon a paper in the Journal Nature about a volumetric display that expanded this one-dimensional standing wave into three dimensions. The paper described using a phased array of ultrasonic transducers, each with a 40 kHz waveform.

After reading the paper and determining how to recreate the experiment, [danfoisy] built a 2D simulation and then another in 3D to validate the approach. We are impressed with the level of physics and programming on display, and that the same code carried through to the build.

[danfoisy] didn’t stop with the simulations, designing and building control boards for each 100 x 100 10 x 10 grid of transducers. Each grid is driven by 2 Intel Cyclone FPGAs and all are fed 3D shapes by a Raspberry Pi Zero W. The volume of the display is 100 mm x 100 mm x 145mm and the positioning of the foam ball is accurate down to .01 mm though currently there is considerable distortion in the positioning.

Check out the video after the break to see the process of simulating, designing, and testing the display. There are a number of tips along the way, including how to test for the polarity of the transducers and the use of a Python script to place the grids of transducers and drivers in KiCad.

danfoisy vdatp schematic  danfoisy vdatp board layout

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Ice40 Runs DOOM

Spec sheets are an important tool in determining the performance of a given part or system, but they’re not the be all and end all when it comes to engineering. However, specs alone don’t prove whether a given system can complete a given task. Sometimes, you need to actually do the work to prove it instead – as [Sylvain] has done, running DOOM on the iCE40 FPGA.

DOOM’s minimum specifications demand a 386 with 4MB RAM minimum, but it’s commonly agreed that a 486 DX2 running at 66MHz with 8MB of RAM is required to play the game smoothly. With an iCEBreaker v1.0b running a RISC V softcore at 25MHz, it may seem like a difficult task, but the RISC V core has the benefit that many instructions run in a single clock cycle that take many on the 486. While the iCEBreaker doesn’t have much RAM onboard, it’s a simple job to piggyback an 8MB SPI device on top of the existing flash storage. Control of the game is via keystrokes sent to the iCEBreaker over serial, while video is handled over a PMOD video interface with an HDMI connector.

[Sylvain] does a great job of explaining all the minute details of the work that was required to get things working, and has provided files on Github for those keen to replicate the feat or expand upon the code. Music is notably absent but MIDI output could likely be achieved without much hassle. “Does it run DOOM?” is still a question asked of many platforms, even the new Nintendo Game & Watch. Video after the break.

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