CUDA是一種高效能計算的語言，其架構是GPGPU (General-purpose computing on graphics processing units Processing Unit)，利用處理圖形任務的圖形處理器來計算原本由中央處理器處理的通用計算任務，這些通用計算常常與圖形處理沒有任何關係，其應用於數據處理的運算量遠大於數據調度和傳輸的需要時，通用圖形處理器在性能上大大超越了傳統的中央處理器應用程序。

CUDA的平行程式其平行架構為SIMT(Single Instruction Multiple Threads) ，概念上平行語言不是一種循序的語言，其寫法對於一般在寫C C++等循序語言的程式設計師來說，門檻相對高很多 。

在本篇論文中，將實作一個以OpenBlock為基礎的圖形介面工具，其機制為，拉取程式塊，以邏輯的方式編排程式塊，來自動產生CUDA部分的困難程式碼，藉以簡化CUDA程式，並降低程式可能會出錯的機率。

Graphics Processing Units (GPUs) have recently gained wide popularity among researchers and developers as accelerators for applications outside the domain of traditional computer graphics.

Parallel programming is difficult because it was typically defined as making many CPUs work together (as in a cluster). Desktop applications have been slow to take advantage of multi-core CPUs due to the difficulty of splitting a single program into one that works across multiple threads. These difficulties arise from the fact that a CPU is inherently a serial processor and having multiple CPUs require complex software to manage them.

We implemented a tool called CUDABlock that enables graphical programming on GPU. This tool enables CUDA source code to be generated automatically and easily.

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