With many cores driven by high memory bandwidth, today＇s graphics processing unit （GPU） has involved into an absolute computing workhorse. More and more scientists, researchers and software developers are using GPU...With many cores driven by high memory bandwidth, today＇s graphics processing unit （GPU） has involved into an absolute computing workhorse. More and more scientists, researchers and software developers are using GPUs to accelerate their algorithms and ap- plications. Developing complex programs and software on the GPU, however, is still far from easy with ex- isting tools provided by hardware vendors. This article introduces our recent research efforts to make GPU soft- ware development much easier. Specifically, we designed BSGP, a high-level programming language for general- purpose computation on the GPU. A BSGP program looks much the same as a sequential C program, and is thus easy to read, write and maintain. Its performance on the GPU is guaranteed by a well-designed compiler that converts the program to native GPU code. We also developed an effective debugging system for BSGP pro- grams based on the GPU interrupt, a unique feature of BSGP that allows calling CPU functions from inside GPU code. Moreover, using BSGP, we developed GPU algorithms for constructing several widely-used spatial hierarchies for high-performance graphics applications.展开更多
文摘With many cores driven by high memory bandwidth, today＇s graphics processing unit （GPU） has involved into an absolute computing workhorse. More and more scientists, researchers and software developers are using GPUs to accelerate their algorithms and ap- plications. Developing complex programs and software on the GPU, however, is still far from easy with ex- isting tools provided by hardware vendors. This article introduces our recent research efforts to make GPU soft- ware development much easier. Specifically, we designed BSGP, a high-level programming language for general- purpose computation on the GPU. A BSGP program looks much the same as a sequential C program, and is thus easy to read, write and maintain. Its performance on the GPU is guaranteed by a well-designed compiler that converts the program to native GPU code. We also developed an effective debugging system for BSGP pro- grams based on the GPU interrupt, a unique feature of BSGP that allows calling CPU functions from inside GPU code. Moreover, using BSGP, we developed GPU algorithms for constructing several widely-used spatial hierarchies for high-performance graphics applications.
