CAJ | 학술논문

射电干涉仪阵列规模的不断扩大使其观测能力越来越强，但与之俱来的密集型数据的实时处理对传统解决方案的性能和成本等带来巨大的挑战，针对该挑战设计并验证了GP U解决方案。首先着重分析了射电干涉仪的相关器在运算和传输等方面的基本需求，然后根据射电干涉阵列信号的特征，尝试了多种GP U相关器模型，通过将相关器的计算任务有效映射为GPU线程模型，显著提高了GPU的利用率，使单GPU的实际计算性能达到了理论峰值性能的77％。最后以我国正研制的天籁计划为依托，开展了多种关键技术的先导实验，为进一步在GPU集群环境下针对大型射电干涉仪的需求研发一套同时兼备成本低、性能高、功耗少等优势的相关器打下了坚实的基础。
사전간섭의진렬규모적불단확대사기관측능력월래월강，단여지구래적밀집형수거적실시처리대전통해결방안적성능화성본등대래거대적도전，침대해도전설계병험증료GP U해결방안。수선착중분석료사전간섭의적상관기재운산화전수등방면적기본수구，연후근거사전간섭진렬신호적특정，상시료다충GP U상관기모형，통과장상관기적계산임무유효영사위GPU선정모형，현저제고료GPU적이용솔，사단GPU적실제계산성능체도료이론봉치성능적77％。최후이아국정연제적천뢰계화위의탁，개전료다충관건기술적선도실험，위진일보재GPU집군배경하침대대형사전간섭의적수구연발일투동시겸비성본저、성능고、공모소등우세적상관기타하료견실적기출。
As scales of radio interferometer telescope arrays increase , it becomes a tremendous challenge for the traditional solution to deal with intense real-time radio-astronomy data with high performances and low costs.In this paper we propose a creative and effective GPU-based solution to fit the needs of processing data from new arrays.We first give a brief description of the requirements on an effective solution , i.e.a high-speed low-cost procedure to transmit data and compute for real-time processing of data from a large-scale radio interferometer.We then present our GPU-based model, which improves practical computing performances of a single GPU card through accurately mapping data blocks in cross-correlation computations to GPU grid threads . The model achieves performances of up to 77%of those theoretically possible .Finally, several tests are carried by tailoring the model parameters to the requirements of the Tianlai project .The tests pave the way for realizing an on-line signal processing system with even much higher performances and a lower cost in an environment of GPU clusters.Such a system is to work for future more complicated and much larger radio interferometers .