SoAx: A generic C++ Structure of Arrays for handling particles in HPC codes
The numerical study of physical problems often require integrating the dynamics of a large number of particles evolving according to a given set of equations. Particles are characterized by the information they are carrying such as an identity, a position other. There are generally speaking two diff...
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| Vydáno v: | Computer physics communications Ročník 224; s. 325 - 332 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.03.2018
Elsevier |
| Témata: | |
| ISSN: | 0010-4655, 1879-2944 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | The numerical study of physical problems often require integrating the dynamics of a large number of particles evolving according to a given set of equations. Particles are characterized by the information they are carrying such as an identity, a position other. There are generally speaking two different possibilities for handling particles in high performance computing (HPC) codes. The concept of an Array of Structures (AoS) is in the spirit of the object-oriented programming (OOP) paradigm in that the particle information is implemented as a structure. Here, an object (realization of the structure) represents one particle and a set of many particles is stored in an array. In contrast, using the concept of a Structure of Arrays (SoA), a single structure holds several arrays each representing one property (such as the identity) of the whole set of particles.
The AoS approach is often implemented in HPC codes due to its handiness and flexibility. For a class of problems, however, it is known that the performance of SoA is much better than that of AoS. We confirm this observation for our particle problem. Using a benchmark we show that on modern Intel Xeon processors the SoA implementation is typically several times faster than the AoS one. On Intel’s MIC co-processors the performance gap even attains a factor of ten. The same is true for GPU computing, using both computational and multi-purpose GPUs.
Combining performance and handiness, we present the library SoAx that has optimal performance (on CPUs, MICs, and GPUs) while providing the same handiness as AoS. For this, SoAx uses modern C++ design techniques such template meta programming that allows to automatically generate code for user defined heterogeneous data structures.
Program Title: SoAx
Program Files doi:http://dx.doi.org/10.17632/m463pc4mv8.1
Licensing provisions: GPLv3
Programming language: C++
Nature of problem: Structures of arrays (SoA) are generally faster than arrays of structures (AoS) while AoS are more handy. This library (SoAx) combines the advantages of both. By means of C++(11) meta-template programming SoAx achieves maximal performance (efficient use of vector units and cache of modern CPUs) while providing a very convenient user interface (including object-oriented element handling) and flexibility. It has been designed to handle list-like sets of particles (similar to struct int id; double[3] pos; float[3] vel;;) in the context of high-performance numerical simulations. It can be applied to many other problems.
Solution method: Template Metaprogramming, Expression Templates |
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| ISSN: | 0010-4655 1879-2944 |
| DOI: | 10.1016/j.cpc.2017.11.015 |