scholarly journals Improving Scalability and Maintenance of Software for High-Performance Scientific Computing by Combining MDE and Frameworks

2011 ◽  
pp. 213-227 ◽  
Author(s):  
Marc Palyart ◽  
David Lugato ◽  
Ileana Ober ◽  
Jean-Michel Bruel
Keyword(s):  
High Performance ◽  
Scientific Computing

scholarly journals Compiler-directed scratchpad memory data transfer optimization for multithreaded applications on a heterogeneous many-core architecture

2021 ◽  
Author(s):  
Xiaohan Tao ◽  
Jianmin Pang ◽  
Jinlong Xu ◽  
Yu Zhu
Keyword(s):  
Energy Consumption ◽  
High Performance ◽  
Scientific Computing ◽  
Data Transfer ◽  
Performance Model ◽  
Experimental Result ◽  
Transfer Model ◽  
Scratchpad Memory ◽  
On Chip ◽  
Many Core

AbstractThe heterogeneous many-core architecture plays an important role in the fields of high-performance computing and scientific computing. It uses accelerator cores with on-chip memories to improve performance and reduce energy consumption. Scratchpad memory (SPM) is a kind of fast on-chip memory with lower energy consumption compared with a hardware cache. However, data transfer between SPM and off-chip memory can be managed only by a programmer or compiler. In this paper, we propose a compiler-directed multithreaded SPM data transfer model (MSDTM) to optimize the process of data transfer in a heterogeneous many-core architecture. We use compile-time analysis to classify data accesses, check dependences and determine the allocation of data transfer operations. We further present the data transfer performance model to derive the optimal granularity of data transfer and select the most profitable data transfer strategy. We implement the proposed MSDTM on the GCC complier and evaluate it on Sunway TaihuLight with selected test cases from benchmarks and scientific computing applications. The experimental result shows that the proposed MSDTM improves the application execution time by 5.49$$\times$$ × and achieves an energy saving of 5.16$$\times$$ × on average.

scholarly journals Implementation of Scientific Computing Applications on the Cell Broadband Engine

2009 ◽  
Vol 17 (1-2) ◽  
pp. 135-151 ◽  
Author(s):  
Guochun Shi ◽  
Volodymyr V. Kindratenko ◽  
Ivan S. Ufimtsev ◽  
Todd J. Martinez ◽  
James C. Phillips ◽  
...  
Keyword(s):  
High Performance ◽  
Scientific Computing ◽  
Lessons Learned ◽  
Optimization Techniques ◽  
Cell Processor ◽  
Intrinsic Properties ◽  
Cell Broadband Engine ◽  
Performance Improvements ◽  
Cell Architecture ◽  
Practical Recommendations

The Cell Broadband Engine architecture is a revolutionary processor architecture well suited for many scientific codes. This paper reports on an effort to implement several traditional high-performance scientific computing applications on the Cell Broadband Engine processor, including molecular dynamics, quantum chromodynamics and quantum chemistry codes. The paper discusses data and code restructuring strategies necessary to adapt the applications to the intrinsic properties of the Cell processor and demonstrates performance improvements achieved on the Cell architecture. It concludes with the lessons learned and provides practical recommendations on optimization techniques that are believed to be most appropriate.

Accelerated Discovery and Design of Nano-Material Applications in Nuclear Power by Using High Performance Scientific Computing

2015 ◽  
pp. 83-118
Author(s):  
Liviu Popa-Simil
Keyword(s):  
Nuclear Power ◽  
High Performance ◽  
Scientific Computing ◽  
Material Behavior ◽  
Nano Materials ◽  
Macro Scale ◽  
Material Systems ◽  
Nano Material ◽  
And Performance

The accelerated development of nano-sciences and nano-material systems and technologies is made possible through the use of High Performance Scientific Computing (HPSC). HPSC exploration ranges from nano-clusters to nano-material behavior at mezzo-scale and specific macro-scale products. These novel nano-materials and nano-technologies developed using HPSC can be applied to improve nuclear devices' safety and performance. This chapter explores the use of HPSC.

Parallel/High-Performance Object-Oriented Scientific Computing

1999 ◽  
pp. 222-239
Author(s):  
Bernd Mohr ◽  
Federico Bassetti ◽  
Kei Davis ◽  
Stefan Hüttemann ◽  
Pascale Launay ◽  
...  
Keyword(s):  
High Performance ◽  
Scientific Computing ◽  
Object Oriented
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