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GPUBIocks: GUI Programming Tool for CUDA and OpenCL

机译:GPUBIocks:用于CUDA和OpenCL的GUI编程工具

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摘要

Recent advances in general-purpose graphics processing units (GPGPUs) have resulted in massively parallel hardware that is widely available to achieve high performance in desktop, notebook, and even mobile computer systems. While multicore technology has become the norm of modern computers, programming such systems requires the understanding of underlying hardware architecture and hence posts a great challenge for average programmers, who might be professionals in specific domains, but not experts in parallel programming. This paper presents a GUI tool called GPUBlocks that can facilitate parallel programming on multicore computer systems. GPUBlocks is developed based on the OpenBlocks framework, an extendable tool for graphical programming, to construct the GUI-based programming environment for CUDA and OpenCL parallel computing platforms. Programmers simply need to drag-n-drop blocks, fill the fields of the blocks, and connect them according to array or matrix computations that are specified by algorithms. GPUBlocks can then translate block-based code to CUDA or OpenCL programs. Furthermore, a couple of optimization constructs have also been offered for rapid program optimization. Experimental results have shown that the generated CUDA and OpenCL programs can achieve reasonable speedups on GPUs. Consequently, GPUBlocks can be used as a tool for fast prototyping of GPU applications or a platform for educational parallel programming.
机译:通用图形处理单元(GPGPU)的最新进展导致了大规模并行硬件的广泛使用,可在台式机,笔记本甚至移动计算机系统中实现高性能。尽管多核技术已成为现代计算机的规范,但对此类系统进行编程需要了解底层硬件体系结构,因此对普通程序员(可能是特定领域的专业人员,但不是并行编程专家)提出了巨大挑战。本文介绍了一种称为GPUBlocks的GUI工具,该工具可以促进在多核计算机系统上进行并行编程。 GPUBlocks是基于OpenBlocks框架开发的,OpenBlocks框架是用于图形化编程的可扩展工具,旨在为CUDA和OpenCL并行计算平台构建基于GUI的编程环境。程序员只需要拖放块,填充块的字段并根据算法指定的数组或矩阵计算将它们连接起来即可。然后,GPU块可以将基于块的代码转换为CUDA或OpenCL程序。此外,还提供了一些优化构造来进行快速程序优化。实验结果表明,生成的CUDA和OpenCL程序可以在GPU上实现合理的加速。因此,GPU块可以用作GPU应用程序快速原型制作的工具或教育并行编程的平台。

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