Recent Enhancements to the SPARTA DSMC Code
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Moore, Stan Gerald↗
Engineering topics
Plimpton, Steve
Publications and source records attributed to Plimpton, Steve.
SPARTA Users Meeting
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Moore, Stan Gerald↗
Algorithmic and GPU enhancements for molecular dynamics in Cabana and LAMMPS
The focus of this milestone was to implement and test new algorithms and optimizations for improved GPU performance by molecular dynamics (MD) and related particle codes. The work was done in the CoPA Cabana library, the CabanaMD mini-app which uses Cabana to implement and benchmark prototypical MD models, and the LAMMPS MD code which is used by the ECP EXAALT project as well as for materials modeling generally. Efforts included (a) implementation of new or optimized algorithms for fundamental MD kernels like neighbor-list building and FFTs which are also widely used in other particle methods, (b) performance testing of data structure layouts for both simple pairwise and computationally intense neural network potentials, (c) optimizations aimed at improving GPU performance for models with small atom counts, and (d) optimizations specific to the SNAP interatomic potential due to its importance for the EXAALT project.
36 MATERIALS SCIENCE↗
CSlib, a library to couple codes via Client/Server messaging
The CSlib is a small, portable library which enables two (or more) independent simulation codes to be coupled, by exchanging messages with each other. Both codes link to the library when they are built, and can them communicate with each other as they run. The messages contain data or instructions that the two codes send back-and-forth to each other. The messaging can take place via files, sockets, or MPI. The latter is a standard distributed-memory message-passing library.
Plimpton, Steve↗
FireHose Streaming Benchmarks
The FireHose Streaming Benchmarks are a suite of stream-processing benchmarks defined to enable comparison of streaming software and hardware, both quantitatively vis-a-vis the rate at which they can process data, and qualitatively by judging the effort involved to implement and run the benchmarks. Each benchmark has two parts. The first is a generator which produces and outputs datums at a high rate in a specific format. The second is an analytic which reads the stream of datums and is required to perform a well-defined calculation on the collection of datums, typically to find anomalous datums that have been created in the stream by the generator. The FireHose suite provides code for the generators, sample code for the analytics (which users are free to re-implement in their own custom frameworks), and a precise definition of each benchmark calculation.
Plimpton, Steve↗