A Proposal to Extend the OpenMP Tasking Model for Heterogeneous Architectures

Ayguadé, Eduard; Badía, Rosa M.; Cabrera, Daniel; Durán, Alejandro; González, Marc; Igual, Francisco D.; Jiménez, Daniel; Labarta, Jesús; Martorell, Xavier; Mayo, Rafael; Perez, Josep M.; Quintana–Ort́ı, Enrique S.

doi:10.1007/978-3-642-02303-3_13

Cited by 56 publications

(27 citation statements)

References 7 publications

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“…The target construct [10] supports heterogeneity and data motion and can be applied to either tasks or functions. It accepts the device clause to express heterogeneity.…”

Section: The Ompss Programming Modelmentioning

confidence: 99%

Self-Adaptive OmpSs Tasks in Heterogeneous Environments

Planas

Badía

Ayguadé

et al. 2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

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Abstract-As new heterogeneous systems and hardware accelerators appear, high performance computers can reach a higher level of computational power. Nevertheless, this does not come for free: the more heterogeneity the system presents, the more complex becomes the programming task in terms of resource management.OmpSs is a task-based programming model and framework focused on the runtime exploitation of parallelism from annotated sequential applications. This paper presents a set of extensions to this framework: we show how the application programmer can expose different specialized versions of tasks (i.e. pieces of specific code targeted and optimized for a particular architecture) and how the system can choose between these versions at runtime to obtain the best performance achievable for the given application. From the results obtained in a multi-GPU system, we prove that our proposal gives flexibility to application's source code and can potentially increase application's performance.

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“…The target construct [10] supports heterogeneity and data motion and can be applied to either tasks or functions. It accepts the device clause to express heterogeneity.…”

Section: The Ompss Programming Modelmentioning

confidence: 99%

Self-Adaptive OmpSs Tasks in Heterogeneous Environments

Planas

Badía

Ayguadé

et al. 2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

Self Cite

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“…W e are currently working to incorporate the dependence graph management of StarSs and the data movement hints onto OpenMP for accelerators, and participating in the definition of the OpenMP standard. 16 In the future, we will continue porting applications to work on TPC and CellMP to further demonstrate their usefulness. We will also move toward the exploitation of GPUs with pragma-based programming models.…”

Section: Cellstreammentioning

confidence: 99%

Parallel Programming Models for Heterogeneous Multicore Architectures

Ferrer

Bellens²,

Beltrán

et al. 2010

IEEE Micro

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“…In an heterogeneous multicore architecture, we need some additional information in order to appropriately assign the execution of the task to any of the available devices, a GPU, an vector unit, FPGA device, ... Our proposals leverages on previous proposals that allow the specification of dependencies between tasks [6], loop blocking transformations specified at the pragma level [7], and the use of accelerators [8], all of them in the scope of OpenMP 3.0. In the following subsections we comment each one of the new pragmas that we use and/or extend in order to consider FPGA-based accelerator architectures.…”

Section: Proposed Openmp Extensionsmentioning

confidence: 99%

OpenMP extensions for FPGA accelerators

Cabrera

Martorell

Gaydadjiev

et al. 2009

2009 International Symposium on Systems, Architectures, Modeling, and Simulation

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Abstract-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 to make it really productive. In addition, the use of these devices as accelerators in multicore, SMPs and ccNUMA architectures adds an additional level of programming complexity in order to specify the offloading of tasks to reconfigurable devices and the interoperability with current shared-memory programming paradigms such as OpenMP. This paper presents extensions to OpenMP 3.0 that try to address this second challenge and an implementation in a prototype runtime system. With these extensions the programmer can easily express the offloading of an already existing reconfigurable binary code (bitstream) hiding all the complexities related with device configuration, bitstream loading, data arrangement and movement to the device memory. Our current prototype implementation targets the SGI Altix systems with RASC blades (based on the Virtex 4 FPGA). We analyze the overheads introduced in this implementation and propose a hybrid host/device operational mode to hide some of these overheads, significantly improving the performance of the applications. A complete evaluation of the system is done with a matrix multiplication kernel, including an estimation considering different FPGA frequencies.

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A Proposal to Extend the OpenMP Tasking Model for Heterogeneous Architectures

Cited by 56 publications

References 7 publications

Self-Adaptive OmpSs Tasks in Heterogeneous Environments

Self-Adaptive OmpSs Tasks in Heterogeneous Environments

Parallel Programming Models for Heterogeneous Multicore Architectures

OpenMP extensions for FPGA accelerators

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