SkePU: a multi-backend skeleton programming library for multi-GPU systems
Proceedings of the fourth international workshop on High-level parallel programming and applications
StarPU: a unified platform for task scheduling on heterogeneous multicore architectures
Concurrency and Computation: Practice & Experience - Euro-Par 2009
Improving programmability of heterogeneous many-core systems via explicit platform descriptions
Proceedings of the 4th International Workshop on Multicore Software Engineering
Offload – automating code migration to heterogeneous multicore systems
HiPEAC'10 Proceedings of the 5th international conference on High Performance Embedded Architectures and Compilers
Optimized composition of performance-aware parallel components
Concurrency and Computation: Practice & Experience
Transparent CPU-GPU collaboration for data-parallel kernels on heterogeneous systems
PACT '13 Proceedings of the 22nd international conference on Parallel architectures and compilation techniques
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We discuss three complementary approaches that can provide both portability and an increased level of abstraction for the programming of heterogeneous multicore systems. Together, these approaches also support performance portability, as currently investigated in the EU FP7 project PEPPHER. In particular, we consider (1) a library-based approach, here represented by the integration of the SkePU C++ skeleton programming library with the StarPU runtime system for dynamic scheduling and dynamic selection of suitable execution units for parallel tasks; (2) a language-based approach, here represented by the Offload-C++ high-level language extensions and Offload compiler to generate platform-specific code; and (3) a component-based approach, specifically the PEPPHER component system for annotating user-level application components with performance metadata, thereby preparing them for performance-aware composition. We discuss the strengths and weaknesses of these approaches and show how they could complement each other in an integrational programming framework for heterogeneous multicore systems.