LPGPU · Low-Power Parallel Computing on GPUs

Massively parallel GPUs are now being used in a great variety of market segments, ranging from video-games,to user interfaces, and to HPC. There are several signs, however, that computer and consumer technologyindustries are faced with major challenges in delivering improved performance and innovation for futureentertainment devices. First, game developers have argued that while GPUs are increasing in performance, thisis not leading to visual quality improvements because GPUs fundamentally restrict their flexibility. Second, thereare signs that GPUs are approaching a power wall", and architecture innovation is required now to circumventthis wall. Third, there is a lack of GPU tools available to compare multi-core processors (CPUs) to GPUs and toperform GPU program transformations to optimize for performance and power. To address these challenges, thisproject brings together commercial tools, applications and GPU designers, with academic researchers to analyzereal-world mass-market software on comparable graphics processor architectures. The project results willhelp the design of next-generation GPUs, games consoles, and mobile phones, and help software developersproduce graphically innovative software in the future.European companies lead in the design of mobile phone CPUs and GPUs, and are world leaders in video-gamestechnology. These companies need to make large investments in R&D for graphics, for which it is vital that theyhave reliable information.The main market areas for increased processor performance over the next few years are graphics andvideo-games. Therefore, the companies in the consortium are world leaders in real-time lighting for computergraphics (Geomerics), video game AI (AIGameDev.com), power-efficient GPU design (Think Silicon) and GPUtools (Codeplay), and the universities in the consortium are leading experts on low-power computer architecture(Uppsala) and parallel applications and multi-core architectures (TUB).The project seeks to achieve: power and bandwidth reductions of 2x or more on real-world software onnext-generation GPUs, as well as GPU architecture designs that are capable of advanced real-time graphicstechniques (such as radiosity and game AI) at power levels suitable for battery-powered devices."