Future generations of Chip Multiprocessors (CMP) will provide dozens or even hundreds of cores inside the chip. Writing applications that benefit from the massive computational power offered by these chips is not going to ...

While cluster computing frameworks are continuously evolving to provide real-time data analysis capabilities, Apache Spark has managed to be at the forefront of big data analytics. Recent studies propose scale-in clusters ...

We propose the Active Compute Memory (ACM), a near-memory-processing architecture capable of performing key–value sort directly in the DRAM. In the ACM architecture, sort is merely the writing of data into memory with one ...

State-of-the-art programming approaches generally have a strict division between intra-node shared memory parallelism and inter-node MPI communication. Tasking with dependencies offers a clean, dependable abstraction for ...

Nowadays, a new parallel paradigm for energy-efficient heterogeneous hardware infrastructures is required to achieve better performance at a reasonable cost on high-performance computing applications. Under this new paradigm, ...

In this paper we present a unified approach for compiling programs for Distributed-Memory Multiprocessors (DMM). Parallelization of sequential programs for DMM is much more difficult to achieve than for shared memory systems ...

Parallelism has become more and more commonplace with the advent of the multicore processors. Although different parallel pro- gramming models have arisen to exploit the computing capabilities of such processors, ...

Convolutional Neural Networks (CNN) are the most popular of deep network models due to their applicability and success in image processing. Although plenty of effort has been made in designing and training better discriminative ...

Reconfigurable computing is one of the paths to explore towards low-power supercomputing. However, programming these reconfigurable devices is not an easy task and still requires significant research and development efforts ...

Tasking is the most significant feature included in the new OpenMP 3.0 standard. It was introduced to handle unstructured parallelism and broaden the range of applications that can be parallelized by OpenMP. This paper ...