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Manual tuning of applications for heterogeneous parallel systems is tedious and complex. Optimizations are often not portable, and the whole process must be repeated when moving to a new system, or sometimes even to a different problem size. Pattern-...

Manycore accelerators offer the potential of significantly improving the performance of scientific applications when offloading compute intensive portions of programs to the accelerators. Directive-based programming models such as OpenACC and OpenMP are ...

This paper presents a novel way to introduce self-configuration and self-optimization autonomic characteristics to algorithmic skeletons using event driven programming techniques. Based on an algorithmic skeleton language, we show that the use of events ...

It is hard to reason about the state of a multicore system-on-chip, because operations on memory need multiple cycles to complete, since cores communicate via an interconnect like a network-on-chip. To simplify programming, atomicity is required, by ...

Achieving optimal performance on the latest multi-core and many-core architectures depends more and more on making efficient use of the hardware's vector processing capabilities. While auto-vectorizing compilers do not require the use of vector ...

This paper presents the design of a compiler for parallel programs expressed as collections of codelets -- blocks of statements intended for distribution over the processing cores of a massively parallel computer system.

Because interactions of codelets ...

This paper proposes a framework for building multi-platform applications in Java for High Performance Computing (HPC). It allows HPC developers to write their programs in Java but dynamically translate part of the programs into C programs using MPI or ...

The subset-sum problem is a well-known NP-complete decision problem. Many parallel algorithms have been developed to solve the problem within a reasonable computation time, and some of them have been implemented on a GPU. However, the GPU ...

With the emergence of social networks and improvements in computational photography, billions of JPEG images are shared and viewed on a daily basis. Desktops, tablets and smartphones constitute the vast majority of hardware platforms used for displaying ...

Graphic Processing Units (GPUs) have been gaining popularity among high-performance users. Certain classes of algorithms benefit greatly from the massive parallelism of GPUs. One such class of algorithms is longest common subsequence (LCS). Combined ...

Multiple sequence alignment is a fundamental tool in bioinformatics, widely used for predicting protein structure and function, reconstructing phylogeny and several other biological sequence analyses. Because it is a NP-hard problem, several studies ...

Many real-world problems in different industrial and economic fields are permutation combinatorial optimization problems. Solving to optimality large instances of these problems, such as the flowshop problem, is a challenge for multi-core computing.

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We present Palirria, a self-adapting work-stealing scheduling method for nested fork/join parallelism that can be used to estimate the number of utilizable workers and self-adapt accordingly. The estimation mechanism is optimized for accuracy, ...

Traditional work-stealing schedulers perform poorly in multi-programmed multi-core architectures, because all the programs tend to use all the cores and thus incur serious core contention. To relieve this problem, this paper proposes a Demand-aware Work-...

As the ongoing scaling of semiconductor technology causing severe increase of on-chip power density in microprocessors, this leads for urgent requirement for power management during each level of computer system design. In this paper, we describe an ...