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Leveraging OpenACC to Compute High-Accuracy Molecular Energies

Janus Juul EriksenFor this interview, I reached out to Janus Juul Eriksen, a Ph.D. fellow at Aarhus University in Denmark. Janus is a chemist by trade without any formal education in computer science; but he is getting up to 12x speed-up compared to his CPU-only code after modifying less than 100 lines of code with one week of programming effort.

How did he do this? He used OpenACC.

OpenACC is a simple, powerful and portable approach for researchers and scientists who need to rapidly boost application performance for faster science while minimizing programming. With OpenACC, the original source code is kept intact, making the implementation intuitively transparent and leaving most of the hard work to the compiler.

NVIDIA recently announced the new OpenACC Toolkit, an all-in-one suite of parallel programming tools, that helps researchers and scientists quickly accelerate applications.

“OpenACC is much easier to learn than OpenMP or MPI. It makes GPU computing approachable for domain scientists,” says Janus. “Our initial OpenACC implementation required only minor efforts, and more importantly, no modifications of our existing CPU implementation.”

Figure 1: The active site of the Bacterial Leucine Transporter (LeuT) protein, on which the LSDalton team has been doing a number of high-accuracy calculations. The LeuT protein belongs to a family of transporters that are linked to neurological diseases.
Figure 1: The active site of the Bacterial Leucine Transporter (LeuT) protein, on which the LSDalton team has been doing a number of high-accuracy calculations. The LeuT protein belongs to a family of transporters that are linked to neurological diseases.

Janus is part of the research team developing the quantum chemistry code LSDalton, a massively parallel and linear-scaling program for the accurate determination of energies and other molecular properties for large molecular systems.

In need of speed, the LSDalton team was awarded an INCITE allocation which gave them access to Oak Ridge National Laboratory’s Titan supercomputer. With this, they needed to find a way to use the power of the supercomputer: enter OpenACC. Demonstrating success on Titan with their GPU-accelerated code, they were recently one of 13 application code projects selected to join the Center for Accelerated Application Readiness (CAAR) program. This means they will be among the first applications to run on Summit, the new supercomputer debuting in 2018 which will deliver more than five times the computational performance of Titan’s 18,688 nodes.

This access will enable the research team to simulate larger molecular structures at higher accuracy, ultimately accelerating discoveries in materials and quantum chemistry.

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CUDA Spotlight: GPU-Accelerated Quantum Chemistry

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This week’s Spotlight is on Professor Todd Martínez of Stanford.

Professor Martínez’ research lies in the area of theoretical chemistry, emphasizing the development and application of new methods which accurately and efficiently capture quantum mechanical effects.

Professor Martínez pioneered the use of GPU technology for computational chemistry, culminating in the TeraChem software package that uses GPUs for first principles molecular dynamics. He is a founder of PetaChem, the company that distributes this software.

NVIDIA: Todd, tell us about TeraChem.
Todd: TeraChem simulates the dynamics and motion of molecules, solving the electronic Schrodinger equation to determine the forces between atoms. This is often called first principles molecular dynamics or ab initio molecular dynamics.

The primary advantage over empirical force fields (for example, often used for protein structure) is that chemical bond rearrangements and electron transfer can be described seamlessly. Continue reading