Manyfold actors: extending the C++ actor framework to heterogeneous many-core machines using OpenCL

Hiesgen, Raphael; Charousset, Dominik; Schmidt, Thomas C.

doi:10.1145/2824815.2824820

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…First steps towards executing OpenCL kernels within the C++ Actor Framework were presented in [13]. The basic concept of an OpenCL Actor in CAF [22] is now re-examined and extended to execute composable actor chains on resident memory, allowing dynamic execution of data parallel operations.…”

Section: Approaches To Heterogeneous Computingmentioning

confidence: 99%

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OpenCL Actors – Adding Data Parallelism to Actor-Based Programming with CAF

Hiesgen

Charousset

Schmidt

2018

Lecture Notes in Computer Science

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The actor model of computation has been designed for a seamless support of concurrency and distribution. However, it remains unspecific about data parallel program flows, while available processing power of modern many core hardware such as graphics processing units (GPUs) or coprocessors increases the relevance of data parallelism for general-purpose computation.In this work, we introduce OpenCL-enabled actors to the C++ Actor Framework (CAF). This offers a high level interface for accessing any OpenCL device without leaving the actor paradigm. The new type of actor is integrated into the runtime environment of CAF and gives rise to transparent message passing in distributed systems on heterogeneous hardware. Following the actor logic in CAF, OpenCL kernels can be composed while encapsulated in C++ actors, hence operate in a multi-stage fashion on data resident at the GPU. Developers are thus enabled to build complex data parallel programs from primitives without leaving the actor paradigm, nor sacrificing performance. Our evaluations on commodity GPUs, an Nvidia TESLA, and an Intel PHI reveal the expected linear scaling behavior when offloading larger workloads. For sub-second duties, the efficiency of offloading was found to largely differ between devices. Moreover, our findings indicate a negligible overhead over programming with the native OpenCL API.computing has been widely recognized as an important optimization strategy. In addition, accelerating coprocessors that better support code branching established on the market.Since not all tasks can benefit from such specialized devices, developers need to distribute work on the various architectural elements. Managing such a heterogeneous runtime environment inherently increases the complexity. While some loop-based computations can be offloaded to GPUs using OpenACC [10] or recent versions of OpenMP [15] with relatively little programming effort, it has been shown that a consistent task-oriented design exploits the available parallelism more efficiently. Corresponding results achieve better performance [27] while they are also applicable to more complex work loads. However, manually orchestrating tasks between multiple devices is an error-prone and complex task.The actor model of computation describes applications in terms of isolated software entities-actorsthat communicate by asynchronous message passing. Actors can be distributed across any number of processors or machines by the runtime system as they are not allowed to share state and thus can always be executed in parallel. The message-based decoupling of software entities further enables actors to run on different devices in a heterogeneous environment. Hence, the actor model can simplify software development by hiding the complexity of heterogeneous and distributed deployments.In this work, we take up our previous contribution [22] about actors programmed with OpenCLthe Open Computing Language standardized by the Khronos Group [41]. We enhance the integration of heterogeneous programming with the C++ ...

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Section: Approaches To Heterogeneous Computingmentioning

confidence: 99%

“…In this work, we take up our previous contribution [22] about actors programmed with OpenCLthe Open Computing Language standardized by the Khronos Group [41]. We enhance the integration of heterogeneous programming with the C++ Actor Framework [11] by a fully effective encapsulation of OpenCL kernels within C++ actors-the OpenCL actor.…”

Section: Introductionmentioning

confidence: 99%

OpenCL Actors – Adding Data Parallelism to Actor-Based Programming with CAF

Hiesgen

Charousset

Schmidt

2018

Lecture Notes in Computer Science

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Revisiting actor programming in C++

Charousset

Hiesgen

Schmidt

2016

Computer Languages, Systems & Structures

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The actor model of computation has gained significant popularity over the last decade. Its high level of abstraction makes it appealing for concurrent applications in parallel and distributed systems. However, designing a real-world actor framework that subsumes full scalability, strong reliability, and high resource efficiency requires many conceptual and algorithmic additives to the original model.In this paper, we report on designing and building CAF, the "C++ Actor Framework". CAF targets at providing a concurrent and distributed native environment for scaling up to very large, highperformance applications, and equally well down to small constrained systems. We present the key specifications and design concepts-in particular a message-transparent architecture, type-safe message interfaces, and pattern matching facilities-that make native actors a viable approach for many robust, elastic, and highly distributed developments. We demonstrate the feasibility of CAF in three scenarios: first for elastic, upscaling environments, second for including heterogeneous hardware like GPGPUs, and third for distributed runtime systems. Extensive performance evaluations indicate ideal runtime behaviour for up to 64 cores at very low memory footprint, or in the presence of GPUs. In these tests, CAF continuously outperforms the competing actor environments Erlang, Charm++, SalsaLite, Scala, ActorFoundry, and even the OpenMPI.

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GPotion: An embedded DSL for GPU programming in Elixir

Du Bois,

Cavalheiro

2023

Proceedings of the XXVII Brazilian Symposium on Programming Languages

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Manyfold actors: extending the C++ actor framework to heterogeneous many-core machines using OpenCL

Cited by 4 publications

References 13 publications

OpenCL Actors – Adding Data Parallelism to Actor-Based Programming with CAF

OpenCL Actors – Adding Data Parallelism to Actor-Based Programming with CAF

Revisiting actor programming in C++

GPotion: An embedded DSL for GPU programming in Elixir

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