Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to co...Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.展开更多
For the purpose of improving efficiency and realizing start–stop function, an electric oil pump(EOP) is integrated into an 8-speed automatic transmission(AT). A mathematical model is built to calculate the transmissi...For the purpose of improving efficiency and realizing start–stop function, an electric oil pump(EOP) is integrated into an 8-speed automatic transmission(AT). A mathematical model is built to calculate the transmission power loss and the hydraulic system leakage. Based on this model, a flow-based control strategy is developed for EOP to satisfy the system flow requirement. This control strategy is verified through the forward driving simulation. The results indicate that there is a best combination for the size of mechanical oil pump(MOP) and EOP in terms of minimum energy consumption. In order to get a quick and smooth starting process, control strategies of the EOP and the on-coming clutch are proposed. The test environment on a prototype vehicle is built to verify the feasibility of the integrated EOP and its control strategies. The results show that the selected EOP can satisfy the flow requirement and a quick and smooth starting performance is achieved in the start–stop function. This research has a high value for the forward design of EOP in automatic transmissions with respect to efficiency improvement and start–stop function.展开更多
基金Project(61170049) supported by the National Natural Science Foundation of ChinaProject(2012AA010903) supported by the National High Technology Research and Development Program of China
文摘Peta-scale high-perfomlance computing systems are increasingly built with heterogeneous CPU and GPU nodes to achieve higher power efficiency and computation throughput. While providing unprecedented capabilities to conduct computational experiments of historic significance, these systems are presently difficult to program. The users, who are domain experts rather than computer experts, prefer to use programming models closer to their domains （e.g., physics and biology） rather than MPI and OpenME This has led the development of domain-specific programming that provides domain-specific programming interfaces but abstracts away some performance-critical architecture details. Based on experience in designing large-scale computing systems, a hybrid programming framework for scientific computing on heterogeneous architectures is proposed in this work. Its design philosophy is to provide a collaborative mechanism for domain experts and computer experts so that both domain-specific knowledge and performance-critical architecture details can be adequately exploited. Two real-world scientific applications have been evaluated on TH-IA, a peta-scale CPU-GPU heterogeneous system that is currently the 5th fastest supercomputer in the world. The experimental results show that the proposed framework is well suited for developing large-scale scientific computing applications on peta-scale heterogeneous CPU/GPU systems.
基金Project(51405010)supported by the National Natural Science Foundation of ChinaProject(2011BAG09B00)supported by the National Science and Technology Support Program of China
文摘For the purpose of improving efficiency and realizing start–stop function, an electric oil pump(EOP) is integrated into an 8-speed automatic transmission(AT). A mathematical model is built to calculate the transmission power loss and the hydraulic system leakage. Based on this model, a flow-based control strategy is developed for EOP to satisfy the system flow requirement. This control strategy is verified through the forward driving simulation. The results indicate that there is a best combination for the size of mechanical oil pump(MOP) and EOP in terms of minimum energy consumption. In order to get a quick and smooth starting process, control strategies of the EOP and the on-coming clutch are proposed. The test environment on a prototype vehicle is built to verify the feasibility of the integrated EOP and its control strategies. The results show that the selected EOP can satisfy the flow requirement and a quick and smooth starting performance is achieved in the start–stop function. This research has a high value for the forward design of EOP in automatic transmissions with respect to efficiency improvement and start–stop function.
