Our Blue Gene Experience

The paper describes our precious short-time opportunity to make some hands-on experience with the Bulgarian IBM Blue Gene/P system, where we tested the parallel scalability of our domain decomposition finite element solver on a greater number of processors and completed experiments with microstructure modelling of geocomposite materials. The tests showed that due to its relatively low computation/communication performance ratio this specific architecture may need optimizations of parallel codes to take advantage of its performance potential

Computing experience with IBM eServer x455 multiprocessor: the NUMA architecture and Itanium 2 processors

The paper presents experience with a novel parallel IBM eServer xSeries 455 installed at the Institute of Geonics CAS, designated for demanding numerical computations, locally distinguished by its eight processors sharing large main memory. In particular, on specific benchmarks it compares performance of its Itanium 2 processors with other systems locally available and refers about problems related to the NUMA architecture of this machine

Matlab paralelně

Matlab is a popular software widely used for technical and scientific computing. Quite recently, its producer The MathWorks released an add-on toolbox enhancing Matlab’s capabilities towards parallel processing. We investigated this environment and developed some parallel Matlab codes for modelling of nonlinear dynamics of rotors. This paper summarizes our (throughout positive) experience

Úvod do paralelního Matlabu

The contribution provides an introduction to the DCT/DCE parallel computing environment which has recently become part of the Matlab software collection. An application from the field of nonlinear dynamics of rotors is presented and selected parallel constructs are introduced. Practical experiments with this application show very good parallel performance and scalability on a local cluster of 8 processors

Využití DCT/DCE v paralelních výpočtech rotorů

Four years ago, The MathWorks, the producer of Matlab, fulfilled the wishes of many users and released the first version of the DCT/DCE tools enhancing Matlab’s capabilities towards parallel processing, to take advantage of the modern multiprocessor/multicore computer architectures. We followed DCT/DCE’s development, investigated this computing environment from the point of view of the “classical” parallel programming and took advantage of it in a set of Matlab codes for modelling of nonlinear dynamics of rotors. This paper summarizes our (throughout positive) experience

Computational clusters

The contribution deals with clusters of workstations in the context of their employment in parallel processing. It focuses on the nowadays very popular systems based on personal computers (so called Beowulf) and using the Linux operating system. On example of parallel solvers we demostrate that their performance is comparable with that of the much more expensive commercial parallel systems

Parallelization on symmetric multiprocessors

The contribution introduces into the programming of demanding applications on multiprocessors with shared memory. It provides an overview of the parallelization alternatives on this architecture and focuses on those which are based on multithreading. The most important tool, recently established standard OpenMP, is shown on an example