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Particle System Benchmark

Problem

While designing a particle system for my game engine I came up with two different particle storage strategies:

  1. Particles for different particle systems are stored contiguously in memory and updated linearly;
  2. Particles for different particle systems are stored in different memory blocks and updated separately.

I also came up with two different SOA particle layouts:

  1. SOA layout. No memory overhead.
    Stream 0 1 2 3
    Position.x 0 1 2 3
    Position.y 0 1 2 3
    Position.z 0 1 2 3
    Velocity.x 0 1 2 3
    Velocity.y 0 1 2 3
    Velocity.z 0 1 2 3
    Color.r 0 1 2 3
    Color.g 0 1 2 3
    Color.b 0 1 2 3
    Color.a 0 1 2 3
    Lifetime 0 1 2 3
  2. Hybrid SOA/AOS layout. 25% memory overhead on position and velocity (in order to support SIMD).
    Stream 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
    Position x₀ y₀ z₀ w₀ x₁ y₁ z₁ w₁ x₂ y₂ z₂ w₂ x₃ y₃ z₃ w₃
    Velocity x₀ y₀ z₀ w₀ x₁ y₁ z₁ w₁ x₂ y₂ z₂ w₂ x₃ y₃ z₃ w₃
    Color r₀ g₀ b₀ a₀ r₁ g₁ b₁ a₁ r₂ g₂ b₂ a₂ r₃ g₃ b₃ a₃
    Lifetime 0 1 2 3

The first storage strategy seemed much more cache-friendly, but since the particle system information is lost, it lacked a few useful properties:

  1. Difficult to pause a specific particle system when it's out of view frustum;
  2. Difficult to make a force or velocity in particle system's local space;
  3. Difficult to cull particles for render with octree/bvh/kd-tree acceleration structure.

To figure out whether there's any real benefit of messing with one shared particle block, I started this benchmark.

Benchmark

200 particle systems, up to 500 simultaneous particles on each particle system.

I don't think I will ever have over 200 particle systems on the screen, so this benchmark is an attempt to replicate a real game scenario. Scalar/AVX2 benchmarks were done out of curiosity about how much AVX2 boosts the particle system. All measurements are in nanoseconds.

Routine CO* SOA Scalar CO SOA AVX2 CO AOS Scalar CO AOS AVX2 NC* SOA Scalar NC SOA AVX2 NC AOS Scalar NC AOS AVX2
Update 264531433 120406133 258164900 131445633 274460900 103556466 272462066 124984866
Emit 8153666 7688600 9332833 7460000 20566100 17359066 20542666 16783933
Kill 45811433 47438366 25554833 27144133 40538966 38558833 37910833 36486466
TOTAL 318670433 175722133 293242800 166263400 363986233 185967166 358752466 205320066

* — CO goes for contiguous, NC goes for non-contiguous. AOS is actually a hybrid SOA/AOS layout.

Variable particle system count, up to 500 simultaneous particles on each particle system.

The previous benchmark showed an obvious AVX2 superiority, so I won't include scalars here.

Count C SOA AVX2 C AOS AVX2 NC SOA AVX2 NC AOS AVX2
10 5789200 7675500 7949200 7709800
25 21781700 19607500 16427700 18713200
50 31647400 40030300 32928000 38558100
75 67198200 59740300 49744700 56692800
100 72690000 80580700 69201100 76474300
250 169725700 208925000 176025600 190859500
500 391392700 458259900 454150100 562782900
750 739342800 719627600 777583800 763290900
1000 948196100 994504900 1042463100 1144094600
1500 1542934000 1680970400 1984370800 2110293600
2000 2246113400 2421090300 2922469100 3055432600
3000 3780697600 4026085600 5027165700 4974465500
5000 6819852000 7470285900 8700716600 8677681600
10000 15029344700 16136407900 17705982300 17937026600
25000 39668431500 42390617200 43988106000 45365968000

Up to 500 particle systems.

Up to 25000 particle systems.

Conclusion

The contiguous storage strategy expectedly outperforms the non-contiguous one by about 10%. The SOA particle layout outperforms hybrid SOA/AOS by about 10% too. I went for a non-contiguous storage strategy and SOA particle layout because the former is much easier to support and extend, even though it's slightly slower, and the latter is faster and more memory efficient.

References

https://www.bfilipek.com/2014/04/flexible-particle-system-start.html

https://www.popcornfx.com/the-popcornfx-script-execution-model/