ONLINE -- MSA Seminar: Heterogeneous parallelization in GROMACS: lessons learned from a decade of using CPUs and GPUs for molecular dynamics

Start
9th June 2020 01:00 PM
End
9th June 2020 02:00 PM
Location
online via BigBlueButton (see link below)

Modular Supercomputing Architectures Seminar

Speaker: Szilárd Páll, KTH Sweden

GROMACS is a versatile open source molecular dynamics (MD) package with a rich set of features, a bottom-up performance oriented design and strong focus on portability. The MD field has been very successful at recruiting GPUs and as an early adopter, GROMACS has targeted GPUs for nearly a decade. This talk will discuss the algorithmic and heterogeneous parallelization components that makes the GROMACS MD engine not only among the fastest, reaching iteration rates in the hundreds of microseconds at peak, but also highly versatile.

I will discuss our bottom-up redesign of fundamental MD algorithms, critical to efficiently target modern SIMD/SIMT architectures. I will also talk about our multi-level parallelization that separately targets each levels of hardware parallelism: SIMD with up to 14 CPU instructions sets, GPUs from all three major vendors, efficient multi-threading, a highly tuned GPU offload layer, multi-level load balancers, and MPI for SPMD/MPMD multi-node parallelization.

The GROMACS GPU offload features have evolved over time, recently adding the ability to offload entire iterations to the GPU while using the CPU to “reverse offload” work back when beneficial, as well as direct GPU communication for strong scaling . However, a core feature remains: heterogeneous parallelization used for flexibility and performance, aiming to make the best use of both CPUs, GPUs and interconnects. This allows GROMACS to efficiently target both homogeneous and heterogeneous systems from laptops to the largest supercomputers.

This seminar is offered online via BigBlueButton at https://webconf.fz-juelich.de/b/and-2jh-qj4 .

In case of difficulties with BigBlueButton, the seminar will be switched to DFNconf streaming at https://www.conf.dfn.de/stream/nr5hm44jym4c4

Last Modified: 18.11.2022