This is the first PDF-Monday. It started as I used Mondays to read up on what happens around OpenCL and I like to share with you. It is a selection of what I find (somewhat) interesting – don’t hesitate to contact me on anything you want to know about accelerated software.
Parallel Programming Models for Real-Time Graphics. A presentation by Aaron Lefohn of Intel. Why a mix of data-, task-, and pipeline-parallel programming works better using hybrid computing (specifically Intel processors with the latest AVX and SSE extensions) than using GPGPU.
The Practical Reality of Heterogeneous Super Computing. A presentation of Rob Farber of NVidia on why discrete GPUs has a great future even if heterogeneous processors hit the market. Nice insights, as you can expect from the author of the latest CUDA-book.
Scalable Simulation of 3D Wave Propagation in Semi-Infinite Domains Using the Finite Difference Method (Thales Luis Rodrigues Sabino, Marcelo Zamith, Diego Brandâo, Anselmo Montenegro, Esteban Clua, Maurício Kischinhevksy, Regina C.P. Leal-Toledo, Otton T. Silveira Filho, André Bulcâo). GPU based cluster environment for the development of scalable solvers for a 3D wave propagation problem with finite difference methods. Focuses on scattering sound-waves for finding oil-fields.
Parallel Programming Concepts – GPU Computing (Frank Feinbube) A nice introduction to CUDA and OpenCL. They missed task-parallel programming on hybrid systems with OpenCL though.
Proposal for High Data Rate Processing and Analysis Initiative (HDRI). Interesting if you want to see a physics project where they did not have decided yet to use GPGPU or a CPU-cluster.
Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers (Naoya Maruyama, Tatsuo Nomura, Kento Sato and Satoshi Matsuoka). A collection of macros for GPGPU, tested on TSUBAME2.