Comparing GPU effectiveness for Unifrac distance compute

UniFrac is a phylogenetic measure of beta-diversity that assesses differences between pairs of microbiome profiles. UniFrac is useful for microbial community analysis because it can account for the evolutionary relationships between microbes present within a sample.

Unifrac 0.20.2, often referred to as Hybrid Unifrac, can run on either CPUs or GPUs. Most of the compute can be performed using either integer or fp32 compute, making it ideal for consumer-grade GPUs.

The PRP is a distributed, Kubernetes based infrastructure that specializes in providing access to consumer-grade GPUs. We thus tested Hybrid Unifrac on several of the available models, to assess the relative effectiveness of the various models.
Two server-grade GPUs (NVIDIA A40 and A100) and two CPUs (Intel Xeon Gold 6230 and AMD EPYC 7252) have also been benchmarked on PRP for comparison.

There is very little difference between a consumer-grade RTX 3090 and the server-grade A40 and A100 for the unweighted Unifrac. The A100 is however significantly faster on the weighted normalized version; the A40 is instead slightly slower than the 3090 there.The older-generation RTX2080TI is also a strong contender on smaller problems, while both the GTX GPUs and the CPUs are significantly slower.