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SoftShell
Softshell, a novel execution model for devices composed of multiple processing cores operating in a single instruction, multiple data fashion, such as graphics processing units (GPUs). The Softshell model is intuitive and more flexible than the kernel-based adaption of the streamprocessingmodel, which is currently the dominant model for general purpose GPU computation. Using the Softshell model, algorithms with a relatively low local degree of parallelism can execute efficiently on massively parallel architectures. Softshell has the following distinct advantages: (1)work can be dynamically issued directly on the device, eliminating the need for synchronization with an external source, i.e., the CPU; (2) its three-tier dynamic scheduler supports arbitrary scheduling strategies, including dynamic priorities and real-time scheduling; and (3) the user can influence, pause, and cancel work already submitted for parallel execution. The Softshell processing model thus brings capabilities to GPU architectures that were previously only known from operating-system designs and reserved for CPU programming.
SoftShell 1.0.3 preview CUDA source (zip)
ScatterAlloc
ScatterAlloc is a dynamic memory allocator for the GPU. It is designed concerning the requirements of massively parallel execution. ScatterAlloc greatly reduces collisions and congestion by scattering memory requests based on hashing. It can deal with thousands of GPU-threads concurrently allocating memory and its execution time is almost independent of the thread count. ScatterAlloc is open source and easy to use in your CUDA projects.
ScatterAlloc 1.0.1 CUDA source (zip)
Volumetric Real-Time Particle-Based Representation of Large Unstructured Tetrahedral Polygon Meshes
Our version of GPUPBVR is a a particle-based volume rendering approach for unstructured, three-dimensional, tetrahedral polygon meshes. We stochastically generate millions of particles per second and project them on the screen in real-time. In contrast to previous rendering techniques of tetrahedral volume meshes, our method does not need a prior depth sorting of geometry. Instead, the rendered image is generated by choosing particles closest to the camera. Furthermore, we use spatial superimposing. Each pixel is constructed from multiple subpixels. This approach not only increases projection accuracy, but allows also a combination of subpixels into one superpixel that creates the well-known translucency effect of volume rendering. We show that our method is fast enough for the visualization of unstructured three-dimensional grids with hard real-time constraints and that it scales well for a high number of particles.
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