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NUMA Optimizations

General Remarks

This project aims at developing programming and optimization strategies to improve data placement on shared memory computers with non-uniform data access characteristics. This includes ccNUMA systems, but also multi-core processors that often have a complex hierarchical cache structure.

C++ programming techniques for High Performance Computing on systems with non-uniform memory access using OpenMP

Diploma thesis at the Externer Link:  Georg Simon Ohm University of Applied Sciences Nuremberg.

Author: Holger Stengel (now RRZE)

Supervisor: Georg Hager (HPC Services).

Abstract: This work develops programming methodologies for C++ that respect the need for optimal NUMA page placement in OpenMP code. An overloaded new[] operator is presented that guarantees proper placement for arrays of objects. Along the same lines, the STL vector<> class can be endowed with an allocator class argument that serves the same purpose. The disadvantages of std::vector<> in terms of performance and usability in a NUMA setting are circumvented by developing a special numa_vector<> container which is compatible with all STL algorithms. Finally, a container with a segmented, padded data structure, including appropriate iterators, allows one to make generic algorithms aware of data segmentation of any kind (including NUMA) without sacrificing performance.

Downloads: PDF: Poster (English), PDF: Thesis (in German).


Project manager:

  • Dr. Georg Hager
    Regionales Rechenzentrum Erlangen
    HPC Services
    Martensstr. 1
    91058 Erlangen
    +49 (0)9131 85 28973

Letzte Änderung: 13. Maerz 2012, Historie

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