8,282 research outputs found
Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS
GROMACS is a widely used package for biomolecular simulation, and over the
last two decades it has evolved from small-scale efficiency to advanced
heterogeneous acceleration and multi-level parallelism targeting some of the
largest supercomputers in the world. Here, we describe some of the ways we have
been able to realize this through the use of parallelization on all levels,
combined with a constant focus on absolute performance. Release 4.6 of GROMACS
uses SIMD acceleration on a wide range of architectures, GPU offloading
acceleration, and both OpenMP and MPI parallelism within and between nodes,
respectively. The recent work on acceleration made it necessary to revisit the
fundamental algorithms of molecular simulation, including the concept of
neighborsearching, and we discuss the present and future challenges we see for
exascale simulation - in particular a very fine-grained task parallelism. We
also discuss the software management, code peer review and continuous
integration testing required for a project of this complexity.Comment: EASC 2014 conference proceedin
Modular Algorithms for Biomolecular Network Alignment
Comparative analysis of biomolecular networks constructed using measurements from different conditions, tissues, and organisms offer a powerful approach to understanding the structure, function, dynamics, and evolution of complex biological systems. The rapidly advancing field of systems biology aims to understand the structure, function, dynamics, and evolution of complex biological systems in terms of the underlying networks of interactions among the large number of molecular participants involved including genes, proteins, and metabolites. In particular, the comparative analysis of network models representing biomolecular interactions in different species or tissues offers an important tool for identifying conserved modules, predicting functions of specific genes or proteins and studying the evolution of biological processes, among other applications.
The primary focus of this dissertation is on the biomolecular network alignment problem: Given two or more network models, the problem is to optimally match the nodes and links in one network with the nodes and links of the other. The Biomolecular Network Alignment (BiNA) Toolkit developed as part of this dissertation provides a set of efficient (in terms of the running time complexity) and accurate (in terms of various evaluation criteria discussed in the literature) network alignment algorithms for biomolecular networks. BiNA is scalable, user-friendly, modular, and extensible for performing alignments on diverse types of biomolecular networks. The algorithm is applicable to (1) undirected graphs in their weighted and unweighted variations (2) undirected graphs in their labeled and unlabeled variations (3) and has been applied to align multiple networks from hundreds of nodes with a few thousand edges to networks with tens of thousands of nodes with millions of edges. The dissertation provides various applications of network comparison tools including how results from such alignments have been utilized to (1) construct phylogenetic trees based on protein-protein interaction networks, and (2) find biochemical pathways involved in ligand recognition in B cells
Improvements to the APBS biomolecular solvation software suite
The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve
the equations of continuum electrostatics for large biomolecular assemblages
that has provided impact in the study of a broad range of chemical, biological,
and biomedical applications. APBS addresses three key technology challenges for
understanding solvation and electrostatics in biomedical applications: accurate
and efficient models for biomolecular solvation and electrostatics, robust and
scalable software for applying those theories to biomolecular systems, and
mechanisms for sharing and analyzing biomolecular electrostatics data in the
scientific community. To address new research applications and advancing
computational capabilities, we have continually updated APBS and its suite of
accompanying software since its release in 2001. In this manuscript, we discuss
the models and capabilities that have recently been implemented within the APBS
software package including: a Poisson-Boltzmann analytical and a
semi-analytical solver, an optimized boundary element solver, a geometry-based
geometric flow solvation model, a graph theory based algorithm for determining
p values, and an improved web-based visualization tool for viewing
electrostatics
More Bang for Your Buck: Improved use of GPU Nodes for GROMACS 2018
We identify hardware that is optimal to produce molecular dynamics
trajectories on Linux compute clusters with the GROMACS 2018 simulation
package. Therefore, we benchmark the GROMACS performance on a diverse set of
compute nodes and relate it to the costs of the nodes, which may include their
lifetime costs for energy and cooling. In agreement with our earlier
investigation using GROMACS 4.6 on hardware of 2014, the performance to price
ratio of consumer GPU nodes is considerably higher than that of CPU nodes.
However, with GROMACS 2018, the optimal CPU to GPU processing power balance has
shifted even more towards the GPU. Hence, nodes optimized for GROMACS 2018 and
later versions enable a significantly higher performance to price ratio than
nodes optimized for older GROMACS versions. Moreover, the shift towards GPU
processing allows to cheaply upgrade old nodes with recent GPUs, yielding
essentially the same performance as comparable brand-new hardware.Comment: 41 pages, 13 figures, 4 tables. This updated version includes the
following improvements: - most notably, added benchmarks for two coarse grain
MARTINI systems VES and BIG, resulting in a new Figure 13 - fixed typos -
made text clearer in some places - added two more benchmarks for MEM and RIB
systems (E3-1240v6 + RTX 2080 / 2080Ti
- …