Exploring HPC and Big Data Convergence: A Graph Processing Study on Intel Knights Landing

The question 'Can big data and HPC infrastructure converge?' has important implications for many operators and clients of modern computing. However, answering it is challenging. The hardware is currently different, and fast evolving: big data uses machines with modest numbers of fat cores per socket, large caches, and much memory, whereas HPC...

Design and Experimental Evaluation of Distributed Heterogeneous Graph-Processing Systems

Graph processing is increasingly used in a variety of domains, from engineering to logistics and from scientific computing to online gaming. To process graphs efficiently, GPU-enabled graph-processing systems such as TOTEM and Medusa exploit the GPU or the combined CPU+GPU capabilities of a single machine. Unlike scalable distributed CPU-based...

On the effective parallel programming of multi-core processors

Multi-core processors are considered now the only feasible alternative to the large single-core processors which have become limited by technological aspects such as power consumption and heat dissipation. However, due to their inherent parallel structure and their diversity, multi-cores are difficult to program. There is a variety of different...

An effective strategy for porting C++ applications on cell

In this paper we present a solution for efficient porting of sequential C++ applications on the Cell B.E. processor. We present our step-by-step approach, focusing on its generality, we provide a set of code templates and optimization guidelines to support the porting, and we include a set of equations to estimate the performance gain of the new...