arXiv subjects

Vipin Sachdeva

Publications and source records attributed to Vipin Sachdeva.

3 recordsLinked to original sources

arXiv2020

Particle Mesh Ewald for Molecular Dynamics in OpenCL on an FPGA Cluster

Molecular Dynamics (MD) simulations play a central role in physics-driven drug discovery. MD applications often use the Particle Mesh Ewald (PME) algorithm to accelerate electrostatic force computations, but efficient parallelization has proven difficult due to the high communication requirements of distributed 3D FFTs. In this paper, we present the design and implementation of a scalable PME algorithm that runs on a cluster of Intel Stratix 10 FPGAs and can handle FFT sizes appropriate to address real-world drug discovery projects (grids up to $128^3$). To our knowledge, this is the first work to fully integrate all aspects of the PME algorithm (charge spreading, 3D FFT/IFFT, and force interpolation) within a distributed FPGA framework. The design is fully implemented with OpenCL for flexibility and ease of development and uses 100 Gbps links for direct FPGA-to-FPGA communications without the need for host interaction. We present experimental data up to 4 FPGAs (e.g., 206 microseconds per timestep for a 65536 atom simulation and $64^3$ 3D FFT), outperforming GPUs. Additionally, we discuss design scalability on clusters with differing topologies up to 64 FPGAs (with expected performance greater than all known GPU implementations) and integration with other hardware components to form a complete molecular dynamics application. We predict best-case performance of 6.6 microseconds per timestep on 64 FPGAs.

cs.AR↗

arXiv2019

Fully Integrated On-FPGA Molecular Dynamics Simulations

The implementation of Molecular Dynamics (MD) on FPGAs has received substantial attention. Previous work, however, has consisted of either proof-of-concept implementations of components, usually the range-limited force; full systems, but with much of the work shared by the host CPU; or prototype demonstrations, e.g., using OpenCL, that neither implement a whole system nor have competitive performance. In this paper, we present what we believe to be the first full-scale FPGA-based simulation engine, and show that its performance is competitive with a GPU (running Amber in an industrial production environment). The system features on-chip particle data storage and management, short- and long-range force evaluation, as well as bonded forces, motion update, and particle migration. Other contributions of this work include exploring numerous architectural trade-offs and analysis on various mappings schemes among particles/cells and the various on-chip compute units. The potential impact is that this system promises to be the basis for long timescale Molecular Dynamics with a commodity cluster.

cs.DC↗

arXiv2017

OpenRBC: A Fast Simulator of Red Blood Cells at Protein Resolution

We present OpenRBC, a coarse-grained molecular dynamics code, which is capable of performing an unprecedented in silico experiment --- simulating an entire mammal red blood cell lipid bilayer and cytoskeleton as modeled by 4 million mesoscopic particles --- using a single shared memory commodity workstation. To achieve this, we invented an adaptive spatial-searching algorithm to accelerate the computation of short-range pairwise interactions in an extremely sparse 3D space. The algorithm is based on a Voronoi partitioning of the point cloud of coarse-grained particles, and is continuously updated over the course of the simulation. The algorithm enables the construction of the key spatial searching data structure in our code, i.e. a lattice-free cell list, with a time and space cost linearly proportional to the number of particles in the system. The position and shape of the cells also adapt automatically to the local density and curvature. The code implements OpenMP parallelization and scales to hundreds of hardware threads. It outperforms a legacy simulator by almost an order of magnitude in time-to-solution and more than 40 times in problem size, thus providing a new platform for probing the biomechanics of red blood cells.

physics.bio-ph↗