MrXL is an example DSL developed for the frontend tutorial. MrXL programs consist of map and reduce operations on arrays. For example, here is an implementation of dot-products:

input avec: int[1024]
input bvec: int[1024]
output dot: int
prodvec := map 16 (a <- avec, b <- bvec) { a * b }
dot := reduce 4 (a, b <- prodvec) 0 { a + b }

The numbers that come right after map and reduce (16 and 4 respectively) are "parallelism factors" that guide the generation of hardware. The explanation on this page is relatively brief; see the frontend tutorial for a more detailed explanation of the language. In particular, the sum of squares example is a good place to start.


First, install the calyx-py library.

The MrXL implementation is in Python and uses Flit. Install Flit (pip install flit or similar), and then type the following after changing your directory to frontend/mrxl:

flit install --symlink

This creates a symbolic link to the present directory and installs the mrxl command line tool.

By default, fud looks for the mrxl executable to enable the mrxl compilation stage. Type fud check to make sure fud reports that the mrxl compiler has been found. If it does not, run the following while still in frontend/mrxl.

fud register mrxl -p fud/

Run fud check again to ensure that fud sees mrxl.

Interpreting MrXL

To run the program through the MrXL interpreter, execute:

mrxl <prog>.mrxl --data <prog> --interpret

where <prog>.mrxl is a file containing MrXL source code and <prog> is a file containing values for all the variables declared as inputs in the MrXL program. The interpreter dumps the output variables, in JSON format, to stdout.

You could try, for example:

mrxl test/dot.mrxl --data test/ --interpret

This is just a baby version of the dot-product implementation we showed at the very top; we have just shortened the input array so you can easily see it in full. Similarly, we also provide add.mrxl and sum.mrxl, along with accompanying <prog> files, under test/. Try playing with the inputs and the operations!

Compiling to Calyx

The dot-product example above shows off features of MrXL that are not yet supported by the compiler. In particular, the compiler does not yet support reduce with a parallelism factor other than 1. This is because MrXL is mostly a pedagogical device, and we want new users of Calyx to try implementing this feature themselves. To learn more about this and other extensions to MrXL, consider working through the frontend tutorial.

To run the compiler and see the Calyx code your MrXL program generates, just drop the --data and --interpret flags. For instance:

mrxl test/dot.mrxl

In order to run the compiler through fud, pass the --from mrxl and --to calyx flags:

fud e --from mrxl <prog.mrxl> --to calyx

And finally, the real prize. In order to compile MrXL to Calyx and then simulate the Calyx code in Verilog, run:

fud e --from mrxl <prog>.mrxl --to dat --through verilog -s <prog>

An aside: MrXL permits a simplified data format, which is what we have been looking at in our <prog> files. Files of this form need to be beefed up with additional information so that Verilog (and similar simulators) can work with them. We did this beefing up "on the fly" in the incantation above, but it is interesting to see the changes we made.

See this with:

mrxl <prog>.mrxl --data <prog> --convert

The output dumped to stdout is exactly this beefed-up data. The changes it makes are:

  1. It adds some boilerplate about the format of the data.
  2. It infers the output variables required by the program and adds data fields for them.
  3. It infers, for each memory, the parallelism factor requested by the program, and then divides the relevant data entries into memory banks.