[PDF] Top 20 Performance prediction and its use in parallel and distributed computing systems

... plication performance prediction ...High Performance Systems Group at the University of Warwick is a state-of-the-art performance prediction system that provides quantitative ... See full document

... to parallel tasks that are computation ...workstation performance (load monitoring); Exchanging this information between workstations (synchronization); Calculating new distributions and making the work ... See full document

... The model was developed using Mathematica which has also been proposed as a characterisation and modelling tool by Patel [Patel92]. Mathematica is well suited for this purpose since it combines all the advantages of ... See full document

... Given the values shown in Table 1, it is now possible to make predictions for the performance of the multigrid codes on greater numbers of processors. In this paper, we consider executing the codes on np = 64 ... See full document

... Parallel computing allows to indicate how different portions of the computation can be executed concurrently in a heterogeneous computing ...high performance of the existed systems may ... See full document

... two well-known production web traces and find that VOVO alone saves up to 42 % while the ad- dition of voltage scaling saves an additional 18 %. Similarly, Chase, et al. [55] use an artificial resource economy to ... See full document

... MPI designed for fine grain case and typical of parallel computing used in large scale simulations – Only change in model parameters are transmitted – In-place implementation – Synchroni[r] ... See full document

... distinguish its straightness and ...the parallel computing ...to use many cores of processors as a ...real parallel machines, it is feasible to use the parallel virtual ... See full document

... Distributed computing refers to the use of distributed systems to solve computational ...A distributed computing system consists of multiple computers that communicate ... See full document

... High Performance Computing (HPC) in Geographic Information System (GIS) domains ...(LIDAR) systems will generate up to 1, 200 P B of data by 2020 ...several distributed archi- tectures to make ... See full document

... the parallel computing environment having low performance it is better to use the static load distribution mode and having high performance it is better to use the dynamic load ... See full document

... about parallel programming with a system like MPI [5, 6] to achieve ...to use distributed_data_objects instead of numpy arrays in existing code must be as straightforward as ...for parallel usage ... See full document

... We use the CUDA programming model (Nvidia, 2013) in or- der to have fine-grained control over our GPU implemen- tation and to be able to explain and improve performance ...the performance behaviour ... See full document

... the parallel jobs instead of threads, it increased load of the parallel computing ...the parallel computing ...job. Parallel computing is used to solve the large problems ... See full document

... • On general principles parallel and distributed computing have different requirements even if sometimes similar functionalities • Apache stack ABDS typically uses distributed computing [r] ... See full document

... heterogeneous parallel architectures, in the upcoming era of IoT and Big Data, there is significant interest in exploiting the ca- pabilities offered by customised heterogeneous hardware such as FPGA, ASIP, MPSoC, ... See full document

... control its partitioning, and to manipulate it using a rich set of ...compute its partitions from data present in stable storage in case of the worst case scenario when all its preceded datasets are ... See full document

... for parallel processing in distributed memory ...has its own set of data, and can communicate directly with other processes by passing data ...is distributed, it is likely that a computation ... See full document

... • On general principles parallel and distributed computing have different requirements even if sometimes similar functionalities • Apache stack ABDS typically uses distributed computing [r] ... See full document

... Latency for Reduce and Gather operations in 32 nodes with 256-way parallelism. The time is for 1 million messages in each parallel unit, with the given message size. For BSP-Object case we do two MPI calls with ... See full document