The February 2017 OpenACC highlights the directives-based programming model for parallel computing, showcasing impressive performance improvements on CPUs and GPUs. New tools and tutorials are introduced, including compiler support and a guide for scientists to effectively utilize GPUs with OpenACC. Upcoming events and hackathons are announced, emphasizing community engagement and continuous development in the field.

1. February 2017
OPENACC MONTHLY
HIGHLIGHTS

2. OpenACC is a directives-
based programming
approach to parallel
computing designed for
performance and portability
on CPUs and GPUs.

3. PERFORMANCE PORTABLE PROGRAMMING MODEL FOR HPC
Powerful
LSDALTON
Simulation of molecular energies
1.0x
11.7x
CPU GPU
Big Performance
CCSD(T) Module, Alanine-3
Titan System: AMD CPU vs Tesla K20X
SpeedupvsCPU
Simple Portable
main()
{
<serial code>
#pragma acc kernels
{
<parallel code>
}
}
Add Simple Compiler Hint ARM
PEZY
POWER
Sunway
x86 CPU
x86 Xeon Phi
NVIDIA GPU
Quicker Development
Lines of Code Modified
<100 Lines
# of Weeks Required
1 Week

4. Learn what’s new with OpenACC this month

5. NEW PGI 2017
Parallel Fortran, C, C++, OpenACC Compilers and Tools
 OpenACC 2.5 for Tesla P100 GPUs and multicore
CPUs; CUDA 8.0 support
 OpenPOWER CPU performance enhancements of
5-10%
 Comprehensive C++14 support
 GNU 6.2 interoperability
 Additional tuned numerical intrinsic functions for
Haswell and Broadwell
DOWNLOAD NOW

6. 3 STEPS TO MORE SCIENCE TUTORIAL
Simple tutorial designed to help scientists to start with GPUs using
libraries and OpenACC directives.
 3 Tutorial Videos:
1. Step 1: Analyze: Use a profiler to identify hot
spots
2. Step 2: Parallelize: Expose Parallelism
3. Step 3: Optimize: Manage data movements
 Free PGI Community Edition
WATCH NOW

7. PAPERS
Acceleration of Element-by-Element Kernel in Unstructured Implicit
Low-order Finite-element Earthquake Simulation using OpenACC
on Pascal GPUs
 “OpenACC porting approach enables high
performance with relatively low
development costs. When comparing eight
K computer nodes and eight NVIDIA Pascal
P100 GPUs, we achieve 23.1 times speedup
for the element-by-element kernel, which
leads to 16.7 times speedup for the 3 x 3
block Jacobi preconditional conjugate
gradient finite-element solver.”
DOWNLOAD NOW

8.  Oak Ridge National Lab on OpenACC being a
user-driven standard: Longtime User Requests
Added to Next Version of OpenACC
 Five Hackathons in 2017 to Train a New
Generation on GPU Accelerated Computing
ARTICLES AND BLOG POSTS
READ NOW
READ NOW

9. CALL FOR PAPERS
EVENT DUE DATE LINK
GPU Hackathon at Brookhaven
National Lab
March 15th
, 2017 https://www.bnl.gov/gpuhackathon/.
2nd International Workshop on
Performance Portable Programming
Models for Accelerators
April 3, 2017
http://www.csm.ornl.gov/workshops/p3
ma2017/

10. UPCOMING HACKATHONS
LOCATION DATE LINK
Forschungzentrum
Juelich, Juelich, Germany March 6th - 10th https://indico-jsc.fz-juelich.de/event/32/
Brookhaven National
Laboratory, Upton, NY
June 5th
– 9th
https://www.bnl.gov/gpuhackathon/.
For complete list of Hackathons visit: https://www.olcf.ornl.gov/training-event/2017-gpu-hackathons/

11. FOR MORE INFORMATION
Visit OpenACC
EXPLORE NOW