PLC 2013 - Multicore and GPU Programming Models, Languages and Compilers Workshop

The developer is challenged to come up with a programming strategy that will cater to the three important pillars of heterogeneous systems; Productivity, Portability, Performance. Software is an expensive investment (especially in a broad commercial context), creating a programming strategy with longevity so that code may be written once and ported easily, so more than one hardware platform may be utilized. Having said that, how to seamlessly execute legacy applications on heterogeneous platforms that consist of general purpose processors and accelerators by hiding the underlying low level details of the platform from the programmer? There are other programming challenges such as exploiting fine grain parallelism and locality-aware scheduling. This workshop aims to bring the programming community together to explore and discuss various options to make programming heterogeneous systems less challenging and more interesting. The workshop seeks to explore programming methodologies in the form of directive-based approaches, language extensions, novel tools and techniques to create a portable, scalable and productive programming environment. This workshop provides a forum for the presentation of research on all aspects of heterogeneous systems programming models, compiler optimizations, language extensions, and software tools for such systems.
Areas of interest include but are not limited to the following topics:
Multicore processors and Heterogeneous systems
Programming models: thread and task based models, data parallel models, stream programming
Language extensions for GPU programming/environments:
C/C++ extensions for GPU programming
OpenMP extensions for Accelerator
OpenCL/CUDA
OpenACC
CAL
OpenHMPP
Compiler optimizations and tuning Heterogeneous systems
SIMDization/Vectorization
Parallelization and locality optimizations
Reducing synchronization and scheduling overheads on GPU and Multicore
Tiling, parametric tiling and offloading
Runtime systems for Heterogeneous systems
Debuggers, and performance analysis tools for Heterogeneous systems
Operating systems and virtual shared memory for Heterogeneous systems
Software tools for discovering parallelism
Application frameworks, Case studies, design patterns, and domain-specific languages for developing manycore applications