Commodity graphics hardware has become increasingly programmable over the last few years but has been limited to fi\u0002xed resource allocation. These architectures handle some workloads well, others poorly; load-balancing to maximize graphics hardware performance has become a critical issue. In this paper, we explore one solution to this problem using compile-time resource allocation. For our experiments, we implement a graphics pipeline on Raw, a tile-based multicore processor. We express both the full graphics pipeline and the shaders using StreamIt, a high-level language based on the stream programming model. The programmer speci\u0002es the number of tiles per pipeline stage, and the StreamIt compiler maps the computation to the Raw architecture. We evaluate our reconfi\u0002gurable architecture using a mix of common rendering tasks with different workloads and improve throughput by 55\u0096157% over a static allocation. Although our early prototype cannot compete in performance against commercial state-of-the-art graphics processors, we believe that this paper describes an important \u0002first step in addressing the load-balancing challenge.<\/p>\n","protected":false},"excerpt":{"rendered":"
Commodity graphics hardware has become increasingly programmable over the last few years but has been limited to fi\u0002xed resource allocation. These architectures handle some workloads well, others poorly; load-balancing to maximize graphics hardware performance has become a critical issue. In this paper, we explore one solution to this problem using compile-time resource allocation. 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