关键词: 通用计算图形处理器（GPGPU）, 统一计算架构（CUDA）, 自动映射, 源到源编译

Abstract: Aiming at the developing and porting difficulties of GPU-based applications, a mapping approach is proposed, which converts serial computing source code into equivalent parallel computing source code. This approach acquires hierarchies of parallelizable loops from serial sources, establishes the correspondence between loop structures and GPU threads, and generates the core function code for GPU. Meanwhile, CPU control code is generated according to read/write attributes of variable references. A compiler prototype is implemented based on this approach, which translates C code into CUDA code automatically. Functionality and performance evaluations of the prototype show that the CUDA code generated is functionally equivalent to the original C code, with significant improvement in performance, thus ?overcomes the difficulty in porting compute-intensive applications to CPU-GPU heterogeneous systems.

Key words: General Purpose Graphic Processing Unit（GPGPU）, Compute Unified Device Architecture（CUDA）, automatic mapping, source to source compile