智能系统学报
智能繫統學報
지능계통학보
CAAI TRANSACTIONS ON INTELLIGENT SYSTEMS
2015年
1期
1-11
,共11页
计算智能%群体智能%演化算法%机器学习%深度学习%图形处理器%GPU通用计算%异构计算%高性能计算
計算智能%群體智能%縯化算法%機器學習%深度學習%圖形處理器%GPU通用計算%異構計算%高性能計算
계산지능%군체지능%연화산법%궤기학습%심도학습%도형처리기%GPU통용계산%이구계산%고성능계산
computational intelligence%swarm intelligence%evolutionary algorithms%machine learning%deep learn-ing%graphics processing unit(GPU)%general purpose computing on GPUs%heterogonous computing%high per-formance computing (HPC)
在日趋复杂的图形处理任务的推动下，GPU已经演化成为具有众多计算核心、计算能力强大的通用计算设备，并被越来越多地应用于图形处理之外的计算领域。 GPU具有高并行、低能耗和低成本的特点，在数据并行度高的计算任务中，相比与传统的CPU平台有着显著的优势。随着GPU体系结构的不断演进以及开发平台的逐步完善，GPU已经进入到高性能计算的主流行列。 GPU通用计算的普及，使个人和小型机构能有机会获得以往昂贵的大型、超级计算机才能提供的计算能力，并一定程度上改变了科学计算领域的格局和编程开发模式。 GPU提供的强大计算能力极大地推动了计算智能的发展，并且已经在深度学习和群体智能优化方法等子领域获得了巨大的成功，更是在图像、语音等领域取得了突破性的进展。随着人工智能技术和方法的不断进步，GPU将在更多的领域获得更加广泛的应用。
在日趨複雜的圖形處理任務的推動下，GPU已經縯化成為具有衆多計算覈心、計算能力彊大的通用計算設備，併被越來越多地應用于圖形處理之外的計算領域。 GPU具有高併行、低能耗和低成本的特點，在數據併行度高的計算任務中，相比與傳統的CPU平檯有著顯著的優勢。隨著GPU體繫結構的不斷縯進以及開髮平檯的逐步完善，GPU已經進入到高性能計算的主流行列。 GPU通用計算的普及，使箇人和小型機構能有機會穫得以往昂貴的大型、超級計算機纔能提供的計算能力，併一定程度上改變瞭科學計算領域的格跼和編程開髮模式。 GPU提供的彊大計算能力極大地推動瞭計算智能的髮展，併且已經在深度學習和群體智能優化方法等子領域穫得瞭巨大的成功，更是在圖像、語音等領域取得瞭突破性的進展。隨著人工智能技術和方法的不斷進步，GPU將在更多的領域穫得更加廣汎的應用。
재일추복잡적도형처리임무적추동하，GPU이경연화성위구유음다계산핵심、계산능력강대적통용계산설비，병피월래월다지응용우도형처리지외적계산영역。 GPU구유고병행、저능모화저성본적특점，재수거병행도고적계산임무중，상비여전통적CPU평태유착현저적우세。수착GPU체계결구적불단연진이급개발평태적축보완선，GPU이경진입도고성능계산적주류행렬。 GPU통용계산적보급，사개인화소형궤구능유궤회획득이왕앙귀적대형、초급계산궤재능제공적계산능력，병일정정도상개변료과학계산영역적격국화편정개발모식。 GPU제공적강대계산능력겁대지추동료계산지능적발전，병차이경재심도학습화군체지능우화방법등자영역획득료거대적성공，경시재도상、어음등영역취득료돌파성적진전。수착인공지능기술화방법적불단진보，GPU장재경다적영역획득경가엄범적응용。
The GPU enjoys the characteristics of high parallelism , low energy consumption and cheap price .Com-pared with the traditional CPU platform , it is especially suitable for tasks with high data parallelism .GPU compu-ting has come into the mainstream of high performance computation ( HPC) due to the emerging of development platforms like CUDA and OpenCL .The GPU's enormous computational power greatly promotes computational intel-ligence .A great success has been achieved in the fields such as deep learning and swarm intelligence optimization , and several breakthroughs have been seen in image , and speech recognition because of GPU .Though suffering some drawbacks, GPUs provide common people and small institutions with enormous computing power .This has changed the set-up of scientific computing and programming model because it could only be provided by expensive super -computers.To help researchers in the field of computational intelligence better utilize GPUs , a detailed survey of GPGPU is given in this paper. First, the characteristics and advantages of GPUs against CPUs are presented .Then we briefly review the development of GPU hardware followed by a survey of the evolution of development tools for GPGPU;special attention is drawn to two major platforms , CUDA and OpenCL .We end this paper with our per-spectives of the challenges and trends of GPGPU .We point out that embedding and cluster are two major trends for GPGPU and as both academia and industry continue to see increasing progress in artificial intelligence , the GPU will be more widely used in more domains .
