Data-triggered Multithreading for Near-Data Processing

Data-centric computing becomes increasingly important because of the rapid growth of application data. In this work, we introduce the DTM (Data-Triggered Multithreading) pro-gramming model that extends the DTT (Data-Triggered Thread) model and is fully compatible with existing C/C++ programs. The DTM model naturally attaches computation to data. Therefore, the runtime system can dynamically allo-cate the computing resource that provides affinity and locality. We demonstrate the potential of DTM model to improve re-sponse time and improve scalability over the traditional mul-tithreaded programming model. 1