Actual trend set by CPU manufacturers and recent developement in the field of graphical processing units (GPUs) offered us the computational power of multi-core and many-core architectures. Database applications can benefit greatly from parallelism; however, many algorithms need to be redesigned and many technical issues need to be solved. In this paper, we have focused on standard relational j...

This paper briefly reports the GeoMFree , a meshfree / meshless software package designed for analyzing the problems of large deformations and crack propagations of rock and soil masses in geotechnics. The GeoMFree is developed based on the meshfree RPIM, and accelerated by exploiting the parallel computing on multi-core CPU and many-core GPU. The GeoMFree is currently being under intensive dev...

The initial objective was to implement a 3D Gaussian beam model on multi-core, high-performance computing hardware in order to support mid and high frequency applications like reverberation modeling and acoustic channel simulation. As graphic processing unit or GPU hardware rapidly emerged as a compelling platform for such work, my objective became to adapt selected acoustic wave propagation mo...

Existing studies show that using single GPU can lead to obtaining significant performance gains. We should be able to achieve further performance speedup if we use more than one GPU. Heterogeneous processors consisting of multiple CPUs and GPUs offer immense potential and are often considered as a leading candidate for porting complex scientific applications. Unfortunately programming heterogen...

With the broad deployment of multicore processors, there are increasing demands to port OpenCL programs written for GPUs onto the multicore processors. However, OpenCL programs written for GPUs cannot run efficiently on multicore processors since GPU-oriented OpenCL programs generally consist of a huge number of threads. This paper presents experimental comparisons of three thread execution met...

This paper discusses problems related to parallel computing applied in economics. It introduces the paradigms of parallel computing and emphasizes the new trends in this field a combination between GPU computing, multicore computing and distributed computing. It also gives examples of problems arising from economics where these parallel methods can be used to speed up the computations.

We argue that programming high-end stream-processing applications requires a form of coordination language that enables the designer to represent interactions between stream-processing functions asynchronously. We further argue that the level of abstraction that current programming tools engender should be drastically increased and present a coordination language and component technology that i...

A paradigm shift from single-core to parallel multi-core processors has occurred over the last couple of years to further increase the performance of processors. Originating in high-performance computing, this trend has quickly reached general purpose and finally also embedded central processing units (CPUs). Continuing advances in chip manufacture will not only allow an increasing number of ho...

Due to increasing transistor density and the high complexity of core design, processor design has reached a point where multi-core architectures are nearly mandatory to push performance. Large single core designs entail problems such as clock skew and power leakage, while smaller fine tuned cores can run at a higher clock rates. Energy efficiency provides a strong drive for heterogeneous design...

The Setting: Computer science and engineering is undergoing a revolution. Computationally very powerful parallel computers, which used to be the luxury of the government and billion-dollar corporations, are already in the laptops and desktops of millions of ordinary users. Computer architects are building existing computer chips with multiple processing cores inside them, as opposed to with sol...