Build Your Own CPU? That’s the Easy Part!

You want to build your own CPU? That’s great fun, but you might find it isn’t as hard as you think. I’ve done several CPUs over the years, and there’s no shortage of other custom CPUs out there ranging from pretty serious attempts to computers made out of discrete chips to computers made with relays. Not to trivialize the attempt, but the real problem isn’t the CPU. It is the infrastructure.

What Kind of Infrastructure?

I suppose the holy grail would be to bootstrap your custom CPU into a full-blown Linux system. That’s a big enough job that I haven’t done it. Although you might be more productive than I am, you probably need a certain amount of sleep, and so you may want to consider if you can really get it all done in a reasonable time. Many custom CPUs, for example, don’t run interactive operating systems (or any operating system, for that matter). In extreme cases, custom CPUs don’t have any infrastructure and you program them in straight machine code.

Machine code is error prone so, you really need an assembler. If you are working on a big machine, you might even want a linker. Assembly language coding gets tedious after a while, so maybe you want a C compiler (or some other language). A debugger? What about an operating system?

Each one of those things is a pretty serious project all by itself (on top of the project of making a fairly capable CPU). Unless you have a lot of free time on your hands or a big team, you are going to have to consider how to hack some shortcuts.

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Open Source FPGA Toolchain Builds CPU

When you develop software, you need some kind of toolchain. For example, to develop for an ARM processor, you need a suitable C compiler, a linker, a library, and a programmer. FPGAs use a similar set of tools. However, instead of converting source code to machine language, these tools map the intent of your source code into configuration of FPGA elements and the connections between them.

There’s some variation, but the basic flow in an FPGA build is to use a synthesizer to convert Verilog or VHDL to a physical design. Then a mapper maps that design to the physical elements available on a particular FPGA. Finally, a place and route step determines how to put those elements in a way that they can be interconnected. The final step is to generate a bitstream the chip understands and somehow loading it to the chip (usually via JTAG or by programming a chip or an external EEPROM).

One problem with making your own tools is that the manufacturers typically hold the bitstream format and other essential details close to their chest. Of course, anything can be reverse engineered (with difficulty) and [James Bowman] was able to build a minimal CPU using  an open source Lattice toolchain. The project relies on several open source projects, including  IceStorm, which provides configuration tools for Lattice iCE40 FPGAs (there is a very inexpensive development platform available for this device).

We’ve covered IceStorm before. The IceStorm project provides three tools: one to produce the chip’s binary format from an ASCII representation (and the reverse conversion), a programmer for the iCEstick and HX8K development boards, and database that tells other open source tools about the device.

Those tools blend with other open source tools to form a complete toolchain–a great example of open source collaboration. Yosys does the synthesis (one of the tools available on the EDAPlayground site). The place and route is done by Arachne. The combined tools are now sufficient to build the J1A CPU and can even run a simple version of Forth. If you’ve ever wanted to play with an FPGA-based CPU design, you now have a $22 hardware option and free tools.

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Learn FPGAs in your Browser

FPGAs aren’t really programmed, they are configured. Most designers use Verilog or VHDL to describe the desired circuit configuration. Developers typically simulate these configurations before committing them to silicon (a good habit, especially if you ever graduate from FPGAs to ASICs where changes are very expensive). That simulation takes a lot of software you have to install and learn, right?

Not necessarily. You can do e-mail, word processing, and PCB layout in your browser. Why not FPGA design? The EDAPlayground website provides two editor views: one for your main “code” and another for the testbench (the simulation driver you use to test your design). You can even open multiple files, if you have a complex design.

Once you’ve entered your Verilog or VHDL (or picked one of many examples) you can run the simulation and see the result right in your browser. No software to install, and–outside of actually learning VHDL or Verilog–not much learning curve.

As [Strauburn], [combinatorylogic], and others commented on our recent post about a VHDL CPU, you can do a lot of learning without ever having your hands on real hardware. The web site gives you access to several different tools (useful if you want to see how your code will behave on different tools) and also many standard verification libraries. There are limited synthesis tools, but honestly, if you want to go to real hardware, you are going to want the vendor tools for the specific FPGA you are using.

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Designing a CPU in VHDL for FPGAs: OMG.

If you’ve been thinking about playing around with FPGAs and/or are interested in CPU design, [Domipheus] has started a blog post series that you should check out. Normally we’d wait until the whole series is done to post about it, but it’s looking so good, that we thought we’d share it with you while it’s still in progress. So far, there are five parts.

minispartan6In Part One, [Domipheus] goes through his rationale and plans for the CPU. If you’re at all interested in following along, this post is a must-read. The summary, though, is that he’s aiming to make a stripped-down 16-bit processor on a Spartan 6+ FPGA with basic arithmetic and control flow, and write an assembler for it.

In Part Two, [Domipheus] goes over the nitty-gritty of getting VHDL code rendered and uploaded to the FPGA, and as an example builds up the CPU’s eight registers. If you’re new to FPGAs, pay special attention to the test bench code at the end of the post. Xilinx’s ISE package makes building a test suite for your FPGA code pretty easy, and given the eventual complexity of the system, it’s a great idea to have tests set up for each stage. Testing will be a recurring theme throughout the rest of the posts.

In Part Three, [Domipheus] works through his choices for the instruction set and starts writes up the instruction set decoder. In Part Four, we get to see an ALU and the jump commands are implemented. Part Five builds up a bare-bones control unit and connects the decoder, ALU, and registers together to do some math and count up.

pipe

We can’t wait for further installments. If you’re interested in this sort of thing, and are following [Domipheus]’s progress, be sure to let him know: we gotta keep him working.

Of course, this isn’t the first time anyone’s built a soft-CPU in an FPGA. (The OMG was added mostly to go along with the other TLAs.) Here’s a tiny one, a big one, and a bizarre one.

Really, Really Retro Computer On An FPGA

[Daniel Bailey] built himself a scaled-down clone of a very early computer in an FPGA. Specifically, he wrote some VHDL code to describe the machine in question, a scaled-down clone of the Manchester Small-Scale Experimental Machine with an 8-bit processor and a whopping 8 bytes of RAM, all of which are displayed on an LED screen. Too cool.

That he can get it to do anything at all with such constraints amazes us. Watch him program it and put it through its paces in the video below the break.

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Solving Rubik’s Cube With An FPGA

For their final project for ECE 5760 at Cornell, [Alex], [Sungjoon], and [Rameez] are solving Rubik’s Cubes. They’re doing it with an FPGA, with homebrew robot arms to twist and turn a rainbow cube into the correct position.

First, the mechanical portion of the build. The team are using a system of three robot arms positioned on the left, right, and back faces of the cube relative to a camera. When a cube is placed in the jaws of this robot, the NTSC camera data is fed into an FPGA, where a Nios II soft core handles the actual detection of the cube faces, the solver algorithm, and the controller to send servo commands to the robot arms.

The algorithm used for solving the cube is CFOP – solve the white cross, the white corners, the middle layer, the top face, and finally the entire cube. In practice, the robot ended up taking between 60-70 moves. This is not the most efficient algorithm; the Thistethwaite algorithm only requires 52 moves. There’s a reason for this apparent inefficiency – the Thistlethwaite algorithm requires large look-up tables.

Once the cube is scanned and the correct moves are computed, the soft core in sends commands out through the FPGA’s GPIO pins. Each cube can be solved in under three minutes after it has been scanned, but the team ran into problems with scanning accuracy. It’s a problem that can be fixed with the right lighting setup and better aberrant cubie detection, and a great final project using FPGAs.

Video demo below.

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An Open Source Toolchain For iCE40 FPGAs

FPGAs are great, but open source they are not. All the players in FPGA land have their own proprietary tools for creating bitstream files, and synthesizing the HDL of your choice for any FPGA usually means agreeing to terms and conditions that nobody reads.

After months of work, and based on the previous work of [Clifford Wolf] and [Mathias Lasser], [Cotton Seed] has released a fully open source Verilog to bitstream development tool chain for the Lattice iCE40LP with support for more devices in the works.

Last March, we saw the reverse engineering of the Lattice ICE40 bitstream, but this is a far cry from a robust, mature development platform. Along with Yosys, also written by [Clifford Wolf] it’s relatively simple to go from Verilog to an FPGA that runs your own code.

Video demo below, and there’s a ton of documentation over on the Project IceStorm project page. You can pick up the relevant dev board for about $22 as well.

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