Ray tracing in Nim

Guest post
This is a guest post by Mamy Ratsimbazafy (mratsim). If you would like to publish articles as a guest author on nim-lang.org then get in touch with us via Twitter or otherwise.

Trace of Radiance

Trace of Radiance is an implementation of Ray Tracing in One Weekend in the Nim programming language.

The goals are:

  • Learn more about ray tracing
  • Have fun
  • Serve as a testbed for my own multithreading runtime, Weave
  • Showcase Nim capabilities

In particular, I am convinced (and obviously biased) that if you want to start a rendering project (ray tracing or otherwise) from scratch, Nim is the best language to use, especially if you are focused on:

  • speed
  • correctness
  • compilation times and compile-time computation
  • approachability and development agility


Rendering is an extremely time-consuming task. Nim is fast, very fast, even faster than C++ from time to time.

Here are two benchmarks:

1. Ray Tracing in One Weekend

From the “Ray Tracing in One Weekend” first book, using:

  • Nim 1.2.0 (GCC 10.1), flag -d:danger
  • C++ with GCC 10.1, flag -O3

On Intel Skylake-X i9-9980XE, overclocked at 4.1 GHz all-core turbo. Compiled in x86-64 mode (SSE2 only); 384x216 image; 100 rays per pixel:

Nim C++
38.577 s 42.303 s

The Nim sources for this benchmark can be retrieved from the first release:

git clone https://github.com/mratsim/trace-of-radiance
cd trace-of-radiance
git checkout v0.1.0
nim c -d:danger --outdir:build trace_of_radiance.nim
./build/trace_of_radiance > image.ppm

2. SmallPT

SmallPT is an even smaller ray tracing project.

Benchmark from Weave multithreading runtime ray tracing demo.

Bench Nim Clang OpenMP GCC 10 OpenMP GCC 8 OpenMP
Single-threaded 4m43.369s 4m51.052s 4m50.934s 4m50.648s
Multithreaded 12.977s 14.428s 2m14.616s 12.244s
Nested-parallel 12.981s      
Parallel speedup 21.83x 20.17x 2.16x 23.74x

Single-threaded Nim is 2.7 % faster than Clang C++.
Multithreaded Nim via Weave is 11.1 % faster Clang C++.

Note: GCC 10 has a significant OpenMP regression!

Here are the steps to reproduce the results. Note that if you run the tests on a different hardware, the results might slightly vary from the ones posted above.

git clone https://github.com/mratsim/weave
cd weave
nimble install -y # install Weave dependencies, here Synthesis, overwriting if asked.

nim -v # Ensure you have nim 1.2.0 or more recent

# Threads on (by default in this repo)
nim c -d:danger -o:build/ray_threaded demos/raytracing/smallpt.nim

# Threads off
nim c -d:danger --threads:off -o:build/ray_single demos/raytracing/smallpt.nim

g++ -O3 -o build/ray_gcc_single demos/raytracing/smallpt.cpp
g++ -O3 -fopenmp -o build/ray_gcc_omp demos/raytracing/smallpt.cpp

clang++ -O3 -o build/ray_clang_single demos/raytracing/smallpt.cpp
clang++ -O3 -fopenmp -o build/ray_clang_omp demos/raytracing/smallpt.cpp

Then run for 300 samples with:

build/ray_threaded 300
# ...
build/ray_clang_omp 300


Distinct types and modeling physical units

Nim is one of the few languages that can properly model physical units and enforce proper usage of those units at compile-time. For example, a vector and a unit vector have the same representation but are distinct types. Unit vectors are auto-convertible to vectors when passed to a function:

  Vec3* = object
    x*, y*, z*: float64

  UnitVector* {.borrow:`.`.} = distinct Vec3
    # The `.` annotation ensures that field access is possible

converter toVec3*(uv: UnitVector): Vec3 {.inline.} =
  ## UnitVector are seamlessly convertible to Vec3 (but not the other way around)

Point3 uses the same internal representation as Vec3 and can borrow (share) the implementation of common operators (i.e. no code-size impact):

type Point3* {.borrow: `.`.} = distinct Vec3
  # The `.` annotation ensures that field access is possible

func `*=`*(a: var Point3, scalar: float64) {.borrow.}
func `*`*(a: Point3, scalar: float64): Point3 {.borrow.}
func `*`*(scalar: float64, a: Point3): Point3 {.borrow.}


  • subtracting 2 points gives a vector,
  • adding a vector to a point gives a point,
  • adding 2 points is disallowed, with an nice custom error message instead of the compiler default errors.
func `-`*(a, b: Point3): Vec3 {.inline.}=
  ## Subtracting one point from another gives a vector
  result.x = a.x - b.x
  result.y = a.y - b.y
  result.z = a.z - b.z

func `+`*(p: Point3, v: Vec3): Point3 {.inline.}=
  ## Adding a vector to a point results in a point
  Point3(Vec3(p) + v)

func `-`*(p: Point3, v: Vec3): Point3 {.inline.}=
  ## Subtracting a vector from a point results in a point
  Point3(Vec3(p) - v)

func `+`*(a, b: Point3): Point3 {.error: "Adding 2 Point3 doesn't make physical sense".}

I also have two types for colors and their attenuations (as a percentage), so you cannot multiply colors:

type Color* {.borrow: `.`.} = distinct Vec3

func `*`*(a, b: Color): Color {.error: "Multiplying 2 Colors doesn't make physical sense".}

type Attenuation* {.borrow: `.`.} = distinct Color

func `*=`*(a: var Attenuation, b: Attenuation) {.inline.} =
  # Multiply a color by a per-channel attenuation factor
  a.x *= b.x
  a.y *= b.y
  a.z *= b.z

func `*`*(a, b: Attenuation): Attenuation {.inline.} =
  # Multiply a color by a per-channel attenuation factor
  result.x = a.x * b.x
  result.y = a.y * b.y
  result.z = a.z * b.z

func `*=`*(a: var Color, b: Attenuation) {.inline.} =
  # Multiply a color by a per-channel attenuation factor
  a.x *= b.x
  a.y *= b.y
  a.z *= b.z

Last but not least, ensure you don’t mix and match degrees and radians, with auto-conversion of radians to float (and degree would stay at a higher level):

  Degrees* = distinct float64
  Radians* = distinct float64

template degToRad*(deg: Degrees): Radians =

template radToDeg*(rad: Radians): Degrees =

# For now we don't create our full safe unit library
# with proper cos/sin/tan radians enforcing
# and auto-convert to float
converter toF64*(rad: Radians): float64 {.inline.} =

Tracking mutability

When using value types (stack objects, seq and strings), Nim requires an explicit var when passing parameters or assigning to a variable for a parameter to be mutable.

This makes it clear what can or can’t move under your feet.

Furthermore, C and C++ developers might be interested to know that when passing a large object (over 12 bytes on 32-bit and 24 bytes on 64-bit platforms), Nim does the Right Thing™ and will pass by reference by default (you can override that on a per-type basis to always pass-by-copy or always by reference). This means that function signatures are motivated by mutability concerns and uncluttered from performance (and performance is great, as proven by the benchmarks).

Tracking side-effects

Nim functions can be declared proc or func.

A func enforces the absence of side-effects or the code will not compile. Some examples of side-effects:

  • (non-deterministic) random functions
  • accessing a global variable
  • multithreading
  • IO

If you have a Heisenbug, it’s likely not in a side-effect free function (unless you corrupt memory).

This is particularly suited to physics and ray tracing computational kernels as physics equations are side-effect free.

Compilation times & Meta-programming

Despite all its features, Nim compiles extremely fast with both C and C++ targets. In particular template metaprogramming has a very low compilation-time cost.

Nim is the language with the widest support for compile-time metaprogramming, including dependently-typed languages.

This is supported by a fast VM that gives Nim the speed of Python at compile-time and is used for:

  • writing domain specific languages
    • state machine generators
    • seamless multidimensional arrays uses, including Einstein summation
    • shader generators
    • SIMD kernel generators
  • compile-time precomputations
  • buffers, vectors, matrices parametrized by integer generics

C and C++ interop

Nim can compile to both C and C++ and seamlessly call libraries written in either language. It can even use CUDA with a bit of configuration to call nvcc.

For example, bindings to SFML, from the Nim website features:

Approachability, productivity & development agility

While Nim offers many advanced features, it does not force you to swim or drown on first approach.
Actually many have reported that Nim felt like a compiled scripting language.


Not all is ponies and rainbows. Nim’s main issue is that it is a very young language with a small ecosystem of supported libraries. That said, you can reuse the C and C++ ecosystem (and Javascript as well, since Nim can also compile to it). As an example, Trace of Radiance supports video output via MP4 since v0.2.0 via a simple 60-line wrapper of a header-only C library.