require the application developer to use a combination of several programming models (e. g., MPI with OpenCL or CUDA) in order to exploit the full compute capability of a system. In this paper, we present dOpenCL (Distributed OpenCL) – a uniform approach to programming distributed heterogeneous systems

In this paper we propose the Merge framework, a general purpose programming model for heterogeneous multi-core systems. The Merge framework replaces current ad hoc approaches to parallel programming on heterogeneous platforms with a rigorous, library-based methodology that can automatically

for heterogeneous systems. In this paper, we present libWater, a uniform approach for programming distributed heterogeneous computing systems. It consists of a simple interface, compliant with the OpenCL programming model, and a runtime system which extends the capabilities of OpenCL beyond single platforms

In most cases the programming models of distributed object-oriented systems have a two-stage or even a three-stage object model with different kinds of objects for values, distributable and non-distributable objects. This allows an efficient implementation for at least non-distributed objects

to provide high performance parallel and distributed computing in heterogeneous systems. The study shows that most projects fit within one of the following parallel programming models: (1) message (or object-) passing, (2) distributed shared address (or object), (3) multi-threaded, and (4) transparent (or

A powerful programming environment for developing distributed applications relies on its ability to abstract away the details of the underlying architecture and present a simplified view to the developer. Along the path to transparency and uniformity lies object orientation, a uniform fine

to meaningful events in a timely manner. Smart supply chains fusing dynamic sensor data with information provided by backend-systems are one such example of event-based enterprise systems. Monitoring their global state in an effective way for runtime governance remains an open research challenge: providing

-world application study from the area of medical imaging to demonstrate the reduced programming effort and competitive performance of SkelCL as compared to OpenCL and CUDA. Besides, we illustrate how SkelCL adapts to large-scale, distributed heterogeneous systems in order to simplify their programming.

Abstract Interprocess communication (IPC) is a well-known technique commonly used by programs running on homogeneous distributed systems. However, it cannot be used readily and efficiently by programs running on heterogeneous distributed systems. This is because it must be given a uniform

and methods could be developed to target the genetic determinants leading to persister formation so as to prevent or reverse persistence [2 ]. Given the number of genes involved in persistence, such an approach may prove difficult. Toward development of treatments for a diversity of persisters, it may