Examples of using Diderot
Mathematica Shell PostScript
Failed to load latest commit information.


Diderot Examples

These example programs demonstrate Diderot language, recently described in a VIS 2015 paper. A much simpler version of the language was described in a PLDI 2012 paper. The programs have been written to help you learn how to use Diderot, and to provide starting points for writing your own Diderot programs.

Diderot is a new language, and you can help improve it. You can test and improve the instructions below on how to build the Diderot compiler, try out the example programs and report any problems or confusion, or contribute new example programs. Join the diderot-language Google group to communicate with us.

Diderot development is partially supported by NSF Grants CCF-1446412 and CCF-1564298, as well as by donations from NVIDIA and AMD.

Once you've built the diderotc compiler (and added it to your path) with the instructions below, you can create executable foo from Diderot program foo.diderot with

diderotc --exec foo.diderot

You can then run the program with:


Some examples benefit from different compilation or execution options, as noted.

The examples below should compile with the "vis15" branch of the compiler, which is the focus of ongoing work. Each example has an introductory README.md (generated from the first comment in the program), and more explanatory comments within the source. The example programs are listed here in order from simple to more complex; the later examples assume you've read through and run earlier examples. The first few examples (through tensor) do not exemplify the kinds of algorithms for which Diderot is designed, but do demonstrate various basic language features. Enjoy!

  • hello: Hello world in Diderot
  • heron: A non-trivial program to find square roots, via Heron's method. Demonstrates input variables, stabilize method, 5-argument lerp(), limiting iterations with the -l option, and compiling with --double.
  • sieve: Sieve of Eratosthenes for finding primes. Demonstrates how strands can die (in a strand collection) and the global update block, which can compute on globals and strand states between per-strand updates.
  • life: Conway's Game of Life. Demonstrates strand communication and snapshots for watching how strand state changes.
  • plot1d: Plots a univariate function reconstructed by convolution of 1-D, possibly with border control, and transformed by lifted functions.
  • unicode: Computes nothing, but comments include a Diderot Unicode cheatsheet, with information about the operators that they represent.
  • tensor: Describes tensor shape, and demonstrates printing, indexing, and multiplication of tensors and user-defined functions.
  • vimg: Viewing, within a window of specified location and orientation, of an image or of some of its derived attributes. Demonstrates having an image dataset as an input variable, univariate colormapping, finding gradients with ∇, inv for matrix inverse, and evals and evecs for eigenvalues and eigenvectors.
  • fs2d: For generating 2D synthetic datasets. Demonstrates computing on globals at initialization-time, uninitialized global inputs, chained else-if conditionals to emulate a switch, and single-expression functions defined with =.
  • iso2d: Sampling isocontours with non-interacting particles using Newton-Raphson iteration, which is legible as such because of Diderot's mathematical notation. Also demonstrates the inside and normalize functions,
  • fs3d: For generating a variety of interesting 3D synthetic datasets; similar to but more complicated than fs2d. Demonstrates a user-defined function for doing quaternion to rotation matrix conversion, and nested conditional expressions.
  • tensor2: Details how differentiation adds indices to the end of tensor shape.
  • mip: For maximum-intensity projections through 3D volumes; Shows a minimal example of setting up a camera and casting rays, and also provides a setting for demonstrating how better reconstruction kernels can make a rendering output be invariant with respect to the sampling grid.
  • dvr: For shaded volume rendering of scalar fields. Shows how continue helps avoid having the main update body be too deeply nested in if tests, and per-component vector multiplication with modulate.
  • circle: Mutually repulsive particles moving on a unit circle, showing strand communication and global reductions, and introducing the program structure used in other particle system examples.
  • sphere: Mutually repulsive particles populating a unit sphere, showing population control with new and die.
  • halftone: Particles with radius determined by an underlying image intensity generate an image half-toning.

Some other directories contain supporting files:

  • data: Small sample datasets that can't be generated by program.
  • cmap: Colormaps

Many of these examples involve some non-trivial use of the shell (bash) to pre-process input data or to post-process results from Diderot, in ways that would normally use a high-level language like Python. However: Diderot does not require shell hacking to get work done. These examples do that only to be as self-contained as possible, so that no additional software is needed to start trying out Diderot. Besides command-line executables, Diderot programs can also be compiled to libraries, which can be called from other software. Some examples of OpenGL-based GUIs around Diderot programs will be shared here soon. Our ongoing work includes simplifying connections between compiled Diderot programs and Python, and simplifying how Diderot programs may be interactively debugged.

Building Diderot and these examples

(0) Create $DDRO_ROOT, a place for everything to go in

To keep things contained, you should create a directory (perhaps ~/ddro) to contain all the other software directories referred to below, and set $DDRO_ROOT to refer to it:

mkdir ddro
cd ddro
export DDRO_ROOT=`pwd`

Note: All shell commands used here assume sh/bash syntax (rather than csh/tcsh).

(1) Prerequisites: Cmake, autoconf, C++11

Cmake is needed to build Teem, and GNU autoconf is need to configure the compilation of Diderot. These utilities can be obtained via apt-get on Ubuntu/Debian Linux, or via Homebrew brew on OSX.

To get Cmake:

  • Linux: sudo apt-get install cmake
  • OSX: brew install cmake
  • In any case, the CMake download page includes "Binary distributions" that have the executable cmake you'll need.

To get the autoconf tools (specifically autoconf and autoheader):

  • Linux: sudo apt-get install autoconf
  • OSX: brew install autoconf You will need autoconf version 2.64 or higher.

The Diderot runtime system is written in C++11 and the code generator also produces C++ code, so you will need to have a modern C++ compiler installed.

(2) Get Standard ML of New Jersey

The Diderot compiler is written in SML/NJ, so you'll need to install that first. You need at least version 110.80 to build the current version of Diderot. You can learn the version of the executable sml by running

sml @SMLversion

There are different ways of getting sml.

On OSX, (using Homebrew). Assuming that brew info smlnj mentions version 110.80 or higher, then

brew install smlnj

(possibly followed by brew link smlnj) should work.

On Ubuntu or Debian Linux, apt-get may work to install a sufficiently recent version. apt-cache policy smlnj reports what version you can get; if that's at or above version 110.80, you can:

sudo apt-get install smlnj
sudo apt-get install ml-lpt

The second apt-get to get ml-lpt is required because without it, the later compilation of the Diderot compiler (with the sml from apt-get) will stop with an error message like driver/sources.cm:16.3-16.18 Error: anchor $ml-lpt-lib.cm not defined.

To install from files at http://smlnj.org: On the SML/NJ Downloads page, go to the topmost "Sofware links: files" link (currently 110.80) to get files needed to install SML/NJ on your platform. On OSX there is an installer package to get executables.

Or, you can compile sml from its source yourself. Doing this on a 64-bit Linux machine requires support for 32-bit executables, since sml is itself a 32-bit program. You will know you're missing 32-bit support if the config/install.sh command below fails with an error message like "SML/NJ requires support for 32-bit executables". How you fix this will vary between different versions of Linux. This is documented at the very bottom of the SML/NJ Installation Instructions.

Then, to compile sml from source files at http://smlnj.org (the wget command is specific to version 110.80; there may now be a newer version):

mkdir $DDRO_ROOT/smlnj
cd $DDRO_ROOT/smlnj
wget http://smlnj.cs.uchicago.edu/dist/working/110.80/config.tgz
tar xzf config.tgz
export SMLNJ_CMD=$DDRO_ROOT/smlnj/bin/sml

Once you believe you have sml installed, it should either be in your path (test this with which sml), or, if you didn't do this when compiling sml with the steps immediately above:

export SMLNJ_CMD=/path/to/your/sml

Subsequent Diderot compilation depends on $SMLNJ_CMD being set if sml is not in your path.

(3) Get Teem

The Diderot run-time depends on Teem. Teem is overdue for a release, but in the mean time you should build it from source with CMake, because Diderot (and these examples) assume the current source (revision r6294 or later).

It is best to build a Teem for Diderot that has none of the optional libraries (PNG, zlib, etc) enabled. Experience has shown that additional library dependencies from Teem will complicate the linking that the Diderot compiler must do to create executables.

To get the Teem source and set the TEEMDDRO variable needed later, run:

svn co https://svn.code.sf.net/p/teem/code/teem/trunk teem-src
mkdir teem-ddro
cd teem-ddro; TEEMDDRO=`pwd`

Then, build Teem and install into teem-ddro:

mkdir $DDRO_ROOT/teem-ddro-build
cd $DDRO_ROOT/teem-ddro-build
cmake -Wno-dev \
      -D CMAKE_BUILD_TYPE=Release \
  -D Teem_PNG=OFF -D Teem_ZLIB=OFF \
make install

To make sure your build works, try:

$DDRO_ROOT/teem-ddro/bin/unu --version

Note that we do not recommend adding this teem-ddro/bin to your path; it's not very useful.

Instead, post-processing of Diderot output often generates PNG images, which means you'll want a separate Teem build that includes PNG and zlib. You get this with:

mkdir $DDRO_ROOT/teem-util
cd $DDRO_ROOT/teem-util; TEEMUTIL=`pwd`
mkdir $DDRO_ROOT/teem-util-build
cd $DDRO_ROOT/teem-util-build
cmake -Wno-dev \
      -D CMAKE_BUILD_TYPE=Release \
  -D Teem_PNG=ON -D Teem_ZLIB=ON \
make install

(The difference with the commands above is the -D Teem_PNG=ON -D Teem_ZLIB=ON). To make sure this build includes the useful libraries, try:

$DDRO_ROOT/teem-util/bin/unu about | tail -n 4

The "Formats available" should include "png", and the "Nrrd data encodings available" should include "gz".

To add these Teem utilities to your path:

export PATH=$DDRO_ROOT/teem-util/bin:${PATH}

This will only have an effect for your current shell, you'll have to take other steps, depending your environment, to ensure that this path is added with every login.

Note that unu dnorm is used by the Diderot compiler to assert a canonical representation of orientation and meta-data in Nrrd arrays to simplify and specialize how that information is incoporated into a compiled Diderot program. You can run unu dnorm (perhaps followed by piping into unu head -) on your own data to see exactly what it will do, or to normalize the meta-data prior to compiling the Diderot program (the normalization is idempotent by definition).

(4) Getting Diderot itself.

With the VIS'15 Diderot paper, work began on merging the various branches of the compiler that had been created to implement the new functionalities described in the paper, relative to the earlier PLDI'12 paper. The ongoing merge effort is available in the vis15 branch, but the earlier branches are also available, as described here.

The source for any Diderot branch should be within $DDRO_ROOT:


An svn co command gets the source for a branch; the only difference in the svn co commands below is the branch name at the end of the URL.

The vis15 branch contains functionality from other branches listed below, and is the focus of ongoing merge work. Pthread support is coming soon. The source is available via:

svn co --username anonsvn --password=anonsvn https://svn.smlnj-gforge.cs.uchicago.edu/svn/diderot/branches/vis15

Before the vis15 branch, the vis12 branch (created with a VIS'12 submission in mind) was the most reliable. It lacks some newer features in vis15, but it does have pthread support.

svn co --username anonsvn --password=anonsvn https://svn.smlnj-gforge.cs.uchicago.edu/svn/diderot/branches/vis12

The vis12-cl branch is the only one with a working OpenCL backend. The vis12 branch's diderotc also advertises a --target=cl option, but it only works in the vis12-cl branch.

svn co --username anonsvn --password=anonsvn https://svn.smlnj-gforge.cs.uchicago.edu/svn/diderot/branches/vis12-cl

The lamont and charisee branches were created to support strand communication (for particle systems) and tensor field operators (based on the EIN internal representation), respectively, but these functionalities have been merged into the vis15 branch.

To configure and build any of these branches, the steps are the same. First go into the source directory for the branch, for example:

cd vis15

And then run:

autoheader -Iconfig
autoconf -Iconfig
./configure --with-teem=$TEEMDDRO
make local-install

Note the use of the $TEEMDDRO variable set above, and the possible (implicit) use of the $SMLNJ_CMD variable also described above.

If autoheader fails with something like:

configure.ac:82: error: Autoconf version 2.64 or higher is required

you'll need to update your autoconf installation. If configure fails with:

checking for nrrdMetaDataNormalize... no
configure: error: "please update your teem installation"

it means that your Teem source checkout is not recent enough; nrrdMetaDataNormalize was added with Teem revision r6294. If the build fails with an error message anchor $ml-lpt-lib.cm not defined, it means the ml-lpt library is missing. This is availble through your package manager (such as sudo apt-get install ml-lpt) or from the SML/NJ Distribution Files page.

Once the configure and build is finished, you can check that it worked by trying:

bin/diderotc --help

One technical note: Unlike the executables created by the Diderot compiler bin/diderotc, bin/diderotc is not itself a stand-alone executable. It is a shell script containing absolute paths to the sml installation and to an architecture-specific binary file in bin/.heap used by sml to compile Diderot. Also, when bin/diderotc compiles the C++ files it generates, it depends on the relative locations of the include and lib directories (peer to bin) created by make local-install.

To compile these examples or any other Didorot programs you write, you should add the new diderotc to your path. Assuming you only want to use the latest (vis15) branch of the compiler, you can do this with:

export PATH=$DDRO_ROOT/vis15/bin:${PATH}

(5) Get the examples:

git clone https://github.com/Diderot-Language/examples.git

(6) Try compiling and running the "hello world" example hello:

cd $DDRO_ROOT/examples/hello
diderotc --exec hello.diderot

Running ./hello should print "hello, world". Every Diderot program, even this trivial one, produces an output file. hello created out.nrrd, a container for a single int. We can check its contents with:

unu save -f text -i out.nrrd

which should show "42". If you've gotten this far, you have successfully built Diderot, and compiled and run a Diderot program!

(7) Try the rest of the examples

The beginning of this README.md lists the examples in a sensible order for reading and experimenting, from simple to complex (after hello is heron). The idea is that later examples build on ideas and features shown in earlier examples.

If you use Diderot for your own research or teaching, please share it with the diderot-language Google group, and consider adding some new examples here.