The
computation of two-electron repulsion integrals (ERIs) is often
the most expensive step of integral-direct self-consistent field methods.
Formally it scales as O(N
4), where N is the number of Gaussian basis functions
used to represent the molecular wave function. In practice, this scaling
can be reduced to O(N
2) or less by neglecting small integrals with screening methods. The
contributions of the ERIs to the Fock matrix are of Coulomb (J) and
exchange (K) type and require separate algorithms to compute matrix
elements efficiently. We previously implemented highly efficient GPU-accelerated
J-matrix and K-matrix algorithms in the electronic structure code
TeraChem. Although these implementations supported the use of multiple
GPUs on a node, they did not support the use of multiple nodes. This
presents a key bottleneck to cutting-edge ab initio simulations of
large systems, e.g., excited state dynamics of photoactive proteins.
We present our implementation of multinode multi-GPU J- and K-matrix
algorithms in TeraChem using the Regent programming language. Regent
directly supports distributed computation in a task-based model and
can generate code for a variety of architectures, including NVIDIA
GPUs. We demonstrate multinode scaling up to 45 GPUs (3 nodes) and
benchmark against hand-coded TeraChem integral code. We also outline
our metaprogrammed Regent implementation, which enables flexible code
generation for integrals of different angular momenta.
The Linac Coherent Light Source (LCLS) is an Xray free electron laser (XFEL) facility enabling the study of the structure and dynamics of single macromolecules. A major upgrade will bring the repetition rate of the X-ray source from 120 to 1 million pulses per second. Exascale high performance computing (HPC) capabilities will be required to process the corresponding data rates. We present SpiniFEL, an application used for structure determination of proteins from single-particle imaging (SPI) experiments. An emerging technique for imaging individual proteins and other large molecular complexes by outrunning radiation damage, SPI breaks free from the need for crystallization (which is difficult for some proteins) and allows for imaging molecular dynamics at near ambient conditions. SpiniFEL is being developed to run on supercomputers in near real-time while an experiment is taking place, so that the feedback about the data can guide the data collection strategy. We describe here how we reformulated the mathematical framework for parallelizable implementation and accelerated the most compute intensive parts of the application. We also describe the use of Pygion, a Python interface for the Legion task-based programming model and compare to our existing MPI+GPU implementation.
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