April 2023
OPENACC AND
OPEN HACKATHONS
MONTHLY HIGHLIGHTS

2
WHO IS OPENACC?
The OpenACC Organization is dedicated to helping the research and
developer community advance science by expanding their accelerated
and parallel computing skills.
3 Areas of Focus
Ecosystem
Development
Training/Education
OpenACC
Specification
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3
silica IFPEN, RMM-DIIS on P100
silica IFPEN, RMM-DIIS on P100
OPENACC SPECIFICATION MOMENTUM
Wide Adoption Across Key HPC Codes
ANSYS Fluent
Gaussian
VASP
LSDalton
MPAS
GAMERA
GTC
XGC
ACME
FLASH
COSMO
Numeca
400+ APPS* USING OPENACC
Prof. Georg Kresse
Computational Materials Physics
University of Vienna
For VASP, OpenACC is the way forward for GPU
acceleration. Performance is similar to CUDA, and
OpenACC dramatically decreases GPU
development and maintenance efforts. We’re
excited to collaborate with NVIDIA and PGI as an
early adopter of Unified Memory.
“ “
VASP
Top Quantum Chemistry and Material Science Code
* Applications in production and development

4
LEARN MORE
Develop skills, build community, and increase your opportunities:
Become an Open Hackathons mentor and help scientists leverage
supercomputers to optimize their codes, explore their AI projects, and
accelerate their discoveries.
OPEN HACKATHONS MENTOR PROGRAM
Help Shape Science with Technology
Becoming a mentor for the Open Hackathons has been a truly rewarding
experience. The targeted pathways help bootstrap your knowledge in a
specific domain while each hackathon challenges you to learn about
different nuances associated with using HPC technologies and apply
your knowledge to solve real-world problems. Expanding your
professional network through interactions with other researchers and
mentors is an added bonus!
“ “
Kevin Griffin, Senior Developer Technology Engineer, NVIDIA
Certified HPC Open Hackathons Mentor

5
UPCOMING OPEN HACKATHONS & BOOTCAMPS
COMPLETE LIST OF EVENTS
Event Date
Call Closes
Event
June 8-9, 2023
May 28, 2023
Python GPU Programming Bootcamp
June 28, 2023
June 14, 2023
Hackathon Readiness Bootcamp: Americas
June 28, 2023
June 14, 2023
Hackathon Readiness Bootcamp: Europe
June 28, 2023
June 6, 2023
Hong Kong AI for Science Bootcamp
June 29, 2023
June 14, 2023
Hackathon Readiness Bootcamp: Asia
July 12, 19-21, 2023
May 24, 2023
NERSC Open Hackathon
July 27-28, 2023
July 4, 2023
NCHC N-Ways to GPU Programming Bootcamp
July 25, August 1-4, 2023
June 20, 2023
Wuhan University Open Hackathon
August 15, 22-24, 2023
May 31, 2023
BNL Open Hackathon
Digital in 2023: Our virtual events continue to offer the same high-touch training and mentorship without the
hassle of travel!

6
READ ARTICLE
Team ASiMoV-CCS, with members from EPCC and Rolls-
Royce, took part in the UK National Open Hackathon to
demonstrate the capability to run the ASiMoV-CCS code,
designed for running large-scale engineering simulations,
on GPUs. The Asimov consortium, led by Rolls-Royce and
EPCC, was awarded an EPSRC Prosperity Partnership
worth £14.7m to develop the next generation of engineering
simulation and modeling techniques. The aim is to develop
the world’s first high-fidelity simulation of a complete gas-
turbine engine during operation.
GLIMPSE FROM THE UK NATIONAL HACKATHON
Driving Next-Gen Engineering

7
READ THE ARTICLE
Fortran still underpins some government systems that require
extensive calculations, including those used for weather and
climate science, medicine, and biomedical science among
others. Researchers at Los Alamos National Laboratory
released a report on April 18th evaluating the long-term risks
of relying on Fortran for mission-critical code supporting
nuclear security. They found several challenges to using
Fortran for another 15 years.
WHAT ARE THE RISKS OF RELYING ON FORTRAN?
Los Alamos National Lab Issues Evaluation Report

8
RESOURCES
To accelerate multiphysics applications, making use of not only GPUs but also FPGAs has been
emerging. Multiphysics applications are simulations involving multiple physical models and
multiple simultaneous physical phenomena. Operations with different performance characteristics
appear in the simulation, making the acceleration of simulation speed using only GPUs difficult.
Therefore, we aim to improve the overall performance of the application by using FPGAs to
accelerate operations with characteristics which cause lower GPU efficiency. However, the
application is currently implemented through multilingual programming, where the computation
kernel running on the GPU is written in CUDA and the computation kernel running on the FPGA is
written in OpenCL. This method imposes a heavy burden on programmers; therefore, we are
currently working on a programming environment that enables to use both accelerators in a GPU–
FPGA equipped high-performance computing (HPC) cluster system with OpenACC. To this end,
we port the entire code only with OpenACC from the CUDA-OpenCL mixture. On this basis, this
study quantitatively investigates the performance of the OpenACC GPU implementation compared
to the CUDA implementation for ARGOT, a radiative transfer simulation code for fundamental
astrophysics which is a multiphysics application. We observe that the OpenACC implementation
achieves performance and scalability comparable to the CUDA implementation on the Cygnus
supercomputer equipped with NVIDIA V100 GPUs.
READ PAPER
Paper: Accelerating Radiative Transfer Simulation
on NVIDIA GPUs with OpenACC
Ryohei Kobayashi, Norihisa Fujita, Yoshiki Yamaguchi, Taisuke
Boku, Kohji Yoshikawa, Makito Abe and Masayuki Umemura

9
RESOURCES
We present thread-safe, highly-optimized lattice Boltzmann implementations,
specifically aimed at exploiting the high memory bandwidth of GPUbased
architectures. At variance with standard approaches to LB coding, the proposed
strategy, based on the reconstruction of the post-collision distribution via
Hermite projection, enforces data locality and avoids the onset of memory
dependencies, which may arise during the propagation step, with no need to
resort to more complex streaming strategies. The thread-safe lattice Boltzmann
achieves peak performances, both in two and three dimensions and it allows to
sensibly reduce the allocated memory ( tens of GigaBytes for order billions
lattice nodes simulations) by retaining the algorithmic simplicity of standard LB
computing. Our findings open attractive prospects for high-performance
simulations of complex flows on GPU-based architectures.
READ PAPER
Paper: Thread-Safe Lattice Boltzmann for High-
Performance Computing on GPUs
Andrea Montessoria, Marco Lauricellab, Adriano Tiribocchib, Mihir
Durvec, Michele La Roccaa, Giorgio Amatid, Fabio Bonaccorsoe, and
Sauro Succi
Figure 4. Velocity field during droplet impact. The color
maps in panels (a-f) stand for the vertical component of the
flow field (values are normalized with the velocity of the
droplet at impact) while the superimposed quivers denote
the direction, verse, and magnitude of the local velocity
field.

10
RESOURCES
Decomposition and solver are the main performance bottlenecks of multi-block structured
CFD simulation involving complex industrial configurations such as aero-engine, shock-
boundary layer interactions, turbulence modeling and so on. In this article, we proposed
several optimization strategies to improve the computing efficiency of multi-block structured
CFD simulation based on Sunway TaihuLight super computing system, including: (1) a load
balancing decomposition approach combined with recursive segmentation of undirected
graphs and block mapping for multi-structured blocks, (2) two-level parallelism that utilizes
MPI+ OpenACC2.0* hybrid parallel paradigms with various performance optimizations such
as data preprocessing, reducing unnecessary loops of subroutine calls, collapse, and tile
syntax, memory access optimization between the main memory and local data memory
(LDM), and (3) a carefully orchestrated pipeline and register communication strategy
between computing processor elements (CPEs) to tackle the dependence of LU-SGS
(Lower-Upper Symmetric Gauss–Seidel). Numerical simulations were conducted to
evaluate the proposed optimization strategies. The results showed that our parallel
implementation provides high load balance and efficiency, achieving a speedup of 8× +for
one loop step, and a speed up of 2× +for strong correlation kernels.
READ PAPER
Paper: Optimization Strategies for Multi-Block Structured
CFD Simulation Based on Sunway TaihuLight
Xiaojing Lv, Wenhao Leng, Zhao Liu, Chengsheng Wu, Fang Li, and
Jiuxiu Xu
Figure 1. The architecture of SW26010 CPU.

11
RESOURCES
Website: OpenHackathons.org
Technical Resources
VISIT SITE
Explore a wealth of resources for parallelization and
accelerated computing across HPC, AI and Big Data.
Review a collection of videos, presentations, GitHub
repos, tutorials, libraries, and more to help you advance
your skills and expand your knowledge.

12
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OPENACC AND HACKATHON UPDATES
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advance science by expanding their accelerated
and parallel computing skills.
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