Molecular Dynamics Range-Limited Force Evaluation Optimized for FPGAs

FPGA Molecular Dynamics was much studied from 2004-2010. Due to limited chip resources of that era, and the inherent variety and complexity of tasks comprising Molecular Dynamics simulations (MD), those FPGA accelerators relied on host or embedded processors to organize and pre-process input and output data. This introduced long latency for data movement between simulation iterations and, as technology advanced, drastically limited performance. Current generation FPGAs are equipped not only with abundant on-chip resources, but also have hardware support for floating point operations; these advances provide an opportunity for creating self-contained MD simulation systems on a single device. In this paper, we demonstrate such a system based on the range-limited force, which comprises 90% of the flops in a typical MD simulation. It features online particle-pair generation, hundreds of force evaluation pipelines, motion update, and particle data migration. We integrate into OpenMM and find that, for a representative dataset (liquid argon with 20K atoms), we can achieve a simulation throughput of 1.4us/day with a single FPGA, more than twice the performance of a comparable generation GPU. The bulk of the work presented here explores the design of an independent MD range-limited force evaluation system tailored for modern FPGAs without data exchange with any off-chip devices. The primary contributions are the designs of the new features, the methods for coupling those features into an integrated system, and, especially, the analysis of the most likely mappings among particles/cells, on-chip memories (BRAMs), and on-chip compute units (pipelines).

[1]  José Mario Martínez,et al.  PACKMOL: A package for building initial configurations for molecular dynamics simulations , 2009, J. Comput. Chem..

[2]  Toshikazu Ebisuzaki,et al.  A Highly Parallelized Special-Purpose Computer for Many-Body Simulations with an Arbitrary Central Force: MD-GRAPE , 1996 .

[3]  Martin C. Herbordt,et al.  Integrating FPGA Acceleration into the Protomol Molecular Dynamics Code: Preliminary Report , 2006, 2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines.

[4]  Klaus Schulten,et al.  Generalized Verlet Algorithm for Efficient Molecular Dynamics Simulations with Long-range Interactions , 1991 .

[5]  Laxmikant V. Kalé,et al.  Scalable molecular dynamics with NAMD , 2005, J. Comput. Chem..

[6]  Martin C. Herbordt,et al.  Performance potential of molecular dynamics simulations on high performance reconfigurable computing systems , 2008 .

[7]  Chen Yang,et al.  HPC on FPGA clouds: 3D FFTs and implications for molecular dynamics , 2017, 2017 27th International Conference on Field Programmable Logic and Applications (FPL).

[8]  Viktor K. Prasanna,et al.  Hardware/Software Approach to Molecular Dynamics on Reconfigurable Computers , 2006, 2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines.

[9]  David E. Shaw,et al.  A fast, scalable method for the parallel evaluation of distance‐limited pairwise particle interactions , 2005, J. Comput. Chem..

[10]  Volodymyr V. Kindratenko,et al.  A case study in porting a production scientific supercomputing application to a reconfigurable computer , 2006, 2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines.

[11]  Martin C. Herbordt,et al.  Accelerating molecular dynamics simulations with configurable circuits , 2005, International Conference on Field Programmable Logic and Applications, 2005..

[12]  Martin C. Herbordt,et al.  Improved Interpolation and System Integration for FPGA-Based Molecular Dynamics Simulations , 2006, 2006 International Conference on Field Programmable Logic and Applications.

[13]  Martin C. Herbordt,et al.  Explicit design of FPGA-based coprocessors for short-range force computations in molecular dynamics simulations , 2008, Parallel Comput..

[14]  Benjamin Humphries,et al.  Design of 3D FFTs with FPGA clusters , 2014, 2014 IEEE High Performance Extreme Computing Conference (HPEC).

[15]  Martin C. Herbordt,et al.  Performance potential of molecular dynamics simulations on high performance reconfigurable computing systems , 2008, 2008 Second International Workshop on High-Performance Reconfigurable Computing Technology and Applications.

[16]  Gerrit Groenhof,et al.  GROMACS: Fast, flexible, and free , 2005, J. Comput. Chem..

[17]  Yongfeng Gu Fpga acceleration of molecular dynamics simulations , 2008 .

[18]  Martin C. Herbordt,et al.  FPGA-Based Multigrid Computation for Molecular Dynamics Simulations , 2007 .

[19]  Martin C. Herbordt,et al.  Efficient particle-pair filtering for acceleration of molecular dynamics simulation , 2009, 2009 International Conference on Field Programmable Logic and Applications.

[20]  Paul Chow,et al.  Reconfigurable molecular dynamics simulator , 2004, 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines.

[21]  Chen Yang,et al.  Novo-G#: Large-scale reconfigurable computing with direct and programmable interconnects , 2016, 2016 IEEE High Performance Extreme Computing Conference (HPEC).

[22]  Jiayi Sheng,et al.  Towards Low-Latency Communication on FPGA Clusters with 3 D FFT Case Study , 2015 .

[23]  J. M. Haile,et al.  Molecular dynamics simulation : elementary methods / J.M. Haile , 1992 .

[24]  Martin C. Herbordt,et al.  FPGA-Accelerated Particle-Grid Mapping , 2016, 2016 IEEE 24th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM).

[25]  Martin C. Herbordt,et al.  Efficient Calculation of Pairwise Nonbonded Forces , 2011, 2011 IEEE 19th Annual International Symposium on Field-Programmable Custom Computing Machines.

[26]  Bryce K. Allen,et al.  Relative Binding Free Energy Calculations in Drug Discovery: Recent Advances and Practical Considerations , 2017, J. Chem. Inf. Model..

[27]  Marc Snir,et al.  A Note on N-Body Computations with Cutoffs , 2004, Theory of Computing Systems.

[28]  Martin C. Herbordt,et al.  Application-Specific Memory Interleaving Enables High Performance in FPGA-based Grid Computations , 2006, 2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines.

[29]  Alan D. George,et al.  Novo‐G#: a multidimensional torus‐based reconfigurable cluster for molecular dynamics , 2016, Concurr. Comput. Pract. Exp..