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/