Brook+, AMD’s extension of the BrookGPU programming environment, has been released in full source code to SourceForge. Brook+ supports an ATI CAL and x86 CPU backend, and allows developers to program GPUs in a C-like stream computing language.

Abstract:

The StreamIt programming model has been proposed to exploit parallelism in streaming applications on general purpose multicore architectures. This model allows programmers to specify the structure of a program as a set of filters that act upon data, and a set of communication channels between them. The StreamIt graphs describe task, data and pipeline parallelism which can be exploited on modern Graphics Processing Units (GPUs), which support abundant parallelism in hardware.

In this paper, we describe the challenges in mapping StreamIt to GPUs and propose an efficient technique to software pipeline the execution of stream programs on GPUs. We formulate this problem—both scheduling and assignment of filters to processors – as an efficient Integer Linear Program (ILP), which is then solved using ILP solvers. We also describe a novel buffer layout technique for GPUs which facilitates exploiting the high memory bandwidth available in GPUs. The proposed scheduling exploits both the scalar units in GPU, to exploit data parallelism, and multiprocessors, to exploit task and pipeline parallelism. Further it takes into consideration the synchronization and bandwidth limitations of GPUs, yielding speedups between 1.87x and 36.83x over a single threaded CPU.

(Abhishek Udupa, R. Govindarajan, Matthew J. Thazhuthaveetil: Software Pipelined Execution of Stream Programs on GPUs, International Symposium on Code Generation and Optimization 2009 (CGO 2009), pages 200–209. DOI 10.1109/CGO.2009.20, direct link to PDF)