High power dissipating artificial intelligence (AI) chips require significant cooling to operate at maximum performance. Current trends regarding the integration of AI, as well as the power/cooling demands of high-per...High power dissipating artificial intelligence (AI) chips require significant cooling to operate at maximum performance. Current trends regarding the integration of AI, as well as the power/cooling demands of high-performing server systems pose an immense thermal challenge for cooling. The use of refrigerants as a direct-to-chip cooling method is investigated as a potential cooling solution for cooling AI chips. Using a vapor compression refrigeration system (VCRS), the coolant temperature will be sub-ambient thereby increasing the total cooling capacity. Coupled with the implementation of a direct-to-chip boiler, using refrigerants to cool AI server systems can materialize as a potential solution for current AI server cooling demands. In this study, a comparison of 8 different refrigerants: R-134a, R-153a, R-717, R-508B, R-22, R-12, R-410a, and R-1234yf is analyzed for optimal performance. A control theoretical VCRS model is created to assess variable refrigerants under the same operational conditions. From this model, the coefficient of performance (COP), required mass flow rate of refrigerant, work required by the compressor, and overall heat transfer coefficient is determined for all 8 refrigerants. Lastly, a comprehensive analysis is provided to determine the most optimal refrigerants for cooling applications. R-717, commonly known as Ammonia, was found to have the highest COP value thus proving to be the optimal refrigerant for cooling AI chips and high-performing server applications.展开更多
This paper presents a multimedia streaming framework called peer-paired pyramid streaming (P3S) which is basically a hybrid client/server and peer-to-peer structure. In P3S, clients are hierarchically organized with t...This paper presents a multimedia streaming framework called peer-paired pyramid streaming (P3S) which is basically a hybrid client/server and peer-to-peer structure. In P3S, clients are hierarchically organized with those at the same level coupled as peer paris. P3S uses some controlled delay between packets that are vulnerable to shared losses to reduce the shared losses. The technique is verified by both theoretical and experimental results.展开更多
文摘High power dissipating artificial intelligence (AI) chips require significant cooling to operate at maximum performance. Current trends regarding the integration of AI, as well as the power/cooling demands of high-performing server systems pose an immense thermal challenge for cooling. The use of refrigerants as a direct-to-chip cooling method is investigated as a potential cooling solution for cooling AI chips. Using a vapor compression refrigeration system (VCRS), the coolant temperature will be sub-ambient thereby increasing the total cooling capacity. Coupled with the implementation of a direct-to-chip boiler, using refrigerants to cool AI server systems can materialize as a potential solution for current AI server cooling demands. In this study, a comparison of 8 different refrigerants: R-134a, R-153a, R-717, R-508B, R-22, R-12, R-410a, and R-1234yf is analyzed for optimal performance. A control theoretical VCRS model is created to assess variable refrigerants under the same operational conditions. From this model, the coefficient of performance (COP), required mass flow rate of refrigerant, work required by the compressor, and overall heat transfer coefficient is determined for all 8 refrigerants. Lastly, a comprehensive analysis is provided to determine the most optimal refrigerants for cooling applications. R-717, commonly known as Ammonia, was found to have the highest COP value thus proving to be the optimal refrigerant for cooling AI chips and high-performing server applications.
基金Supported by the National Natural Science Foundation of China(No.G1999032700)
文摘This paper presents a multimedia streaming framework called peer-paired pyramid streaming (P3S) which is basically a hybrid client/server and peer-to-peer structure. In P3S, clients are hierarchically organized with those at the same level coupled as peer paris. P3S uses some controlled delay between packets that are vulnerable to shared losses to reduce the shared losses. The technique is verified by both theoretical and experimental results.
