It can be observed from looking backward that processor architecture is improved through spirally shifting from simple to complex and from complex to simple. Nowadays we are facing another shifting from complex to sim...It can be observed from looking backward that processor architecture is improved through spirally shifting from simple to complex and from complex to simple. Nowadays we are facing another shifting from complex to simple, and new innovative architecture will emerge to utilize the continuously increasing transistor budgets. The growing importance of wire delays, changing workloads, power consumption, and design/verification complexity will drive the forthcoming era of Chip Multiprocessors （CMPs）. Furthermore, typical CMP projects both from industries and from academics are investigated. Through going into depths for some primary theoretical and implementation problems of CMPs, the great challenges and opportunities to future CMPs are presented and discussed. Finally, the Godson series microprocessors designed in China are introduced.展开更多
General-purpose processor （GPP） is an important platform for fast Fourier transform （FFT）,due to its flexibility,reliability and practicality.FFT is a representative application intensive in both computation and m...General-purpose processor （GPP） is an important platform for fast Fourier transform （FFT）,due to its flexibility,reliability and practicality.FFT is a representative application intensive in both computation and memory access,optimizing the FFT performance of a GPP also benefits the performances of many other applications.To facilitate the analysis of FFT,this paper proposes a theoretical model of the FFT processing.The model gives out a tight lower bound of the runtime of FFT on a GPP,and guides the architecture optimization for GPP as well.Based on the model,two theorems on optimization of architecture parameters are deduced,which refer to the lower bounds of register number and memory bandwidth.Experimental results on different processor architectures （including Intel Core i7 and Godson-3B） validate the performance model.The above investigations were adopted in the development of Godson-3B,which is an industrial GPP.The optimization techniques deduced from our performance model improve the FFT performance by about 40%,while incurring only 0.8% additional area cost.Consequently,Godson-3B solves the 1024-point single-precision complex FFT in 0.368 μs with about 40 Watt power consumption,and has the highest performance-per-watt in complex FFT among processors as far as we know.This work could benefit optimization of other GPPs as well.展开更多
A non-photorealistic rendering technique is a method to show various effects different from those of realistic image generation.Of the various techniques,flow-based image abstraction displays the shape and color featu...A non-photorealistic rendering technique is a method to show various effects different from those of realistic image generation.Of the various techniques,flow-based image abstraction displays the shape and color features well and performs a stylistic visual abstraction.But real-time rendering is impossible when CPU is used because it applies various filtering and iteration methods.In this paper,we present real-time processing methods of video abstraction using open open computing language(OpenCL),technique of general-purpose computing on graphics processing units(GPGPU).Through the acceleration of general-purpose computing(GPU),16 frame-per-second(FPS)or greater is shown to process video abstraction.展开更多
Artificial general intelligence (AGI) is the ability of an artificial intelligence (AI) agent to solve somewhat-arbitrary tasks in somewhat-arbitrary environments. Despite being a long-standing goal in the field of AI...Artificial general intelligence (AGI) is the ability of an artificial intelligence (AI) agent to solve somewhat-arbitrary tasks in somewhat-arbitrary environments. Despite being a long-standing goal in the field of AI, achieving AGI remains elusive. In this study, we empirically assessed the generalizability of AI agents by applying a deep reinforcement learning (DRL) approach to the medical domain. Our investigation involved examining how modifying the agent’s structure, task, and environment impacts its generality. Sample: An NIH chest X-ray dataset with 112,120 images and 15 medical conditions. We evaluated the agent’s performance on binary and multiclass classification tasks through a baseline model, a convolutional neural network model, a deep Q network model, and a proximal policy optimization model. Results: Our results suggest that DRL agents with the algorithmic flexibility to autonomously vary their macro/microstructures can generalize better across given tasks and environments.展开更多
This study presents a parallel version of the string matching algorithms research tool(SMART)library,implemented on NVIDIA’s compute unified device architecture(CUDA)platform,and uses general-purpose computing on gra...This study presents a parallel version of the string matching algorithms research tool(SMART)library,implemented on NVIDIA’s compute unified device architecture(CUDA)platform,and uses general-purpose computing on graphics processing unit(GPGPU)programming concepts to enhance performance and gain insight into the parallel versions of these algorithms.We have developed the CUDA-enhanced SMART(CUSMART)library,which incorporates parallelized iterations of 64 string matching algorithms,leveraging the CUDA application programming interface.The performance of these algorithms has been assessed across various scenarios to ensure a comprehensive and impartial comparison,allowing for the identification of their strengths and weaknesses in specific application contexts.We have explored and established optimization techniques to gauge their influence on the performance of these algorithms.The results of this study highlight the potential of GPGPU computing in string matching applications through the scalability of algorithms,suggesting significant performance improvements.Furthermore,we have identified the best and worst performing algorithms in various scenarios.展开更多
This paper introduces the microarchitecture and physical implementation of the Godson-2E processor, which is a four-issue superscalar RISC processor that supports the 64-bit MIPS instruction set. The adoption of the a...This paper introduces the microarchitecture and physical implementation of the Godson-2E processor, which is a four-issue superscalar RISC processor that supports the 64-bit MIPS instruction set. The adoption of the aggressive out-of-order execution and memory hierarchy techniques help Godson-2E to achieve high performance. The Godson-2E processor has been physically designed in a 7-metal 90nm CMOS process using the cell-based methodology with some bitsliced manual placement and a number of crafted cells and macros. The processor can be run at 1GHz and achieves a SPEC CPU2000 rate higher than 500.展开更多
Alias – Wavefront OBJ meshes are a common text file type for transferring 3D mesh data between applications made by different vendors.However, as the mesh complexity gets higher and denser, the files become larger an...Alias – Wavefront OBJ meshes are a common text file type for transferring 3D mesh data between applications made by different vendors.However, as the mesh complexity gets higher and denser, the files become larger and slower to import.This paper explores the use of GPUs to accelerate the importing and parsing of OBJ files by studying file read-time, runtime, and load resistance. We propose a new method of reading and parsing that circumvents GPU architecture limitations and improves performance, seeing the new GPU method outperforms CPU methods with a 6×– 8× speedup. When running on a heavily loaded system, the new method only received an 80% performance hit, compared to the160% that the CPU methods received. The loaded GPU speedup compared to unloaded CPU methods was3.5×, and, when compared to loaded CPU methods,8×. These results demonstrate that the time is right for further research into the use of data-parallel GPU acceleration beyond that of computer graphics and high performance computing.展开更多
基金Supported by the National Natural Science Foundation of China for Distinguished Young Scholar under Grant No. 60325205 the National High Technology Development 863 Program of China under Grants No. 2002AA110010, No. 2005AA110010 No. 2005AA119020, and the National Grand Fundamental Research 973 Program of China under Grant No. 2005CB321600.
文摘It can be observed from looking backward that processor architecture is improved through spirally shifting from simple to complex and from complex to simple. Nowadays we are facing another shifting from complex to simple, and new innovative architecture will emerge to utilize the continuously increasing transistor budgets. The growing importance of wire delays, changing workloads, power consumption, and design/verification complexity will drive the forthcoming era of Chip Multiprocessors （CMPs）. Furthermore, typical CMP projects both from industries and from academics are investigated. Through going into depths for some primary theoretical and implementation problems of CMPs, the great challenges and opportunities to future CMPs are presented and discussed. Finally, the Godson series microprocessors designed in China are introduced.
基金supported by the National Science and Technology Major Project under Grant Nos.2009ZX01028-002-003,2009ZX01029-001-003,2010ZX01036-001-002the National Natural Science Foundation of China under Grant Nos.61050002,61003064,60921002
文摘General-purpose processor （GPP） is an important platform for fast Fourier transform （FFT）,due to its flexibility,reliability and practicality.FFT is a representative application intensive in both computation and memory access,optimizing the FFT performance of a GPP also benefits the performances of many other applications.To facilitate the analysis of FFT,this paper proposes a theoretical model of the FFT processing.The model gives out a tight lower bound of the runtime of FFT on a GPP,and guides the architecture optimization for GPP as well.Based on the model,two theorems on optimization of architecture parameters are deduced,which refer to the lower bounds of register number and memory bandwidth.Experimental results on different processor architectures （including Intel Core i7 and Godson-3B） validate the performance model.The above investigations were adopted in the development of Godson-3B,which is an industrial GPP.The optimization techniques deduced from our performance model improve the FFT performance by about 40%,while incurring only 0.8% additional area cost.Consequently,Godson-3B solves the 1024-point single-precision complex FFT in 0.368 μs with about 40 Watt power consumption,and has the highest performance-per-watt in complex FFT among processors as far as we know.This work could benefit optimization of other GPPs as well.
文摘A non-photorealistic rendering technique is a method to show various effects different from those of realistic image generation.Of the various techniques,flow-based image abstraction displays the shape and color features well and performs a stylistic visual abstraction.But real-time rendering is impossible when CPU is used because it applies various filtering and iteration methods.In this paper,we present real-time processing methods of video abstraction using open open computing language(OpenCL),technique of general-purpose computing on graphics processing units(GPGPU).Through the acceleration of general-purpose computing(GPU),16 frame-per-second(FPS)or greater is shown to process video abstraction.
文摘Artificial general intelligence (AGI) is the ability of an artificial intelligence (AI) agent to solve somewhat-arbitrary tasks in somewhat-arbitrary environments. Despite being a long-standing goal in the field of AI, achieving AGI remains elusive. In this study, we empirically assessed the generalizability of AI agents by applying a deep reinforcement learning (DRL) approach to the medical domain. Our investigation involved examining how modifying the agent’s structure, task, and environment impacts its generality. Sample: An NIH chest X-ray dataset with 112,120 images and 15 medical conditions. We evaluated the agent’s performance on binary and multiclass classification tasks through a baseline model, a convolutional neural network model, a deep Q network model, and a proximal policy optimization model. Results: Our results suggest that DRL agents with the algorithmic flexibility to autonomously vary their macro/microstructures can generalize better across given tasks and environments.
基金Project supported by the Scientific and Technological Research Council of Türkiye(No.117E142)Open access funding provided by the Scientific and Technological Research Council of Türkiye(TÜBİTAK)。
文摘This study presents a parallel version of the string matching algorithms research tool(SMART)library,implemented on NVIDIA’s compute unified device architecture(CUDA)platform,and uses general-purpose computing on graphics processing unit(GPGPU)programming concepts to enhance performance and gain insight into the parallel versions of these algorithms.We have developed the CUDA-enhanced SMART(CUSMART)library,which incorporates parallelized iterations of 64 string matching algorithms,leveraging the CUDA application programming interface.The performance of these algorithms has been assessed across various scenarios to ensure a comprehensive and impartial comparison,allowing for the identification of their strengths and weaknesses in specific application contexts.We have explored and established optimization techniques to gauge their influence on the performance of these algorithms.The results of this study highlight the potential of GPGPU computing in string matching applications through the scalability of algorithms,suggesting significant performance improvements.Furthermore,we have identified the best and worst performing algorithms in various scenarios.
基金Supported by the National Natural Science Foundation of China for Distinguished Young Scholars under Grant No. 60325205, the National Natural Science Foundation of China under Grant No. 60673146, the National High Technology Development 863 Program of China under Grants No. 2002AAl10010, No. 2005AAl10010, No. 2005AAl19020, and the National Grand Fundamental Research 973 Program of China under Grant No. 2005CB321600.
文摘This paper introduces the microarchitecture and physical implementation of the Godson-2E processor, which is a four-issue superscalar RISC processor that supports the 64-bit MIPS instruction set. The adoption of the aggressive out-of-order execution and memory hierarchy techniques help Godson-2E to achieve high performance. The Godson-2E processor has been physically designed in a 7-metal 90nm CMOS process using the cell-based methodology with some bitsliced manual placement and a number of crafted cells and macros. The processor can be run at 1GHz and achieves a SPEC CPU2000 rate higher than 500.
文摘Alias – Wavefront OBJ meshes are a common text file type for transferring 3D mesh data between applications made by different vendors.However, as the mesh complexity gets higher and denser, the files become larger and slower to import.This paper explores the use of GPUs to accelerate the importing and parsing of OBJ files by studying file read-time, runtime, and load resistance. We propose a new method of reading and parsing that circumvents GPU architecture limitations and improves performance, seeing the new GPU method outperforms CPU methods with a 6×– 8× speedup. When running on a heavily loaded system, the new method only received an 80% performance hit, compared to the160% that the CPU methods received. The loaded GPU speedup compared to unloaded CPU methods was3.5×, and, when compared to loaded CPU methods,8×. These results demonstrate that the time is right for further research into the use of data-parallel GPU acceleration beyond that of computer graphics and high performance computing.
