俄亥俄州立大学（OSU）多名计算机工程全奖博士生 (2025秋)
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俄亥俄州立大学（OSU）招收多名计算机工程全奖博士生 (2025秋)。OSU在最近的USNEWS 2025排名中计算机工程Computer Engineering排名全美国24，EE排名全美20。所在地哥伦布是俄亥俄州府，两百多万人口，在美国城市排名14位，算中等城市。欢迎有计算机系统，计算机体系结构，移动和嵌入式计算，和计算机软件等背景的同学前来申请。老师是正教授，IEEE Fellow。
The power-aware computer systems (PACS) lab at The Ohio State University (OSU) has multiple fully-funded GRA positions available immediately for self-motivated students to pursue Ph.D. degrees in Computer Engineering.
Our lab recently received multiple NSF grants to do cutting-edge research on making computer systems more energy-efficient to support sustainable AI, which includes several aspects, such as GPU data center, mobile computing, and real-time embedded systems. For GPU data center, we manage the resources of a large number of GPUs to process machine learning or deep learning workloads in a highly energy-efficient way. For mobile computing, we apply machine learning algorithms to improve the performance and energy efficiency of mobile devices, like smartphones or IoT devices. For real-time embedded systems, it is about how to schedule real-time applications, such as autonomous driving tasks, on embedded GPUs to meet real-time deadlines.
"The constraints on AI compute are very predictable...... A year ago, the shortage was chips......Then, the next shortage will be electricity. They won't be able to find enough electricity to run all the chips. I think next year, you'll see they just can't find enough electricity to run all the chips." said Elon Musk in March 2024.
Interested students please directly contact the professor as early as possible for full consideration of the GRA positions.
u.osu.edu
The power-aware computer systems (PACS) lab at The Ohio State University (OSU) has multiple fully-funded GRA positions available immediately for self-motivated students to pursue Ph.D. degrees in Computer Engineering.
Our lab recently received multiple NSF grants to do cutting-edge research on making computer systems more energy-efficient to support sustainable AI, which includes several aspects, such as GPU data center, mobile computing, and real-time embedded systems. For GPU data center, we manage the resources of a large number of GPUs to process machine learning or deep learning workloads in a highly energy-efficient way. For mobile computing, we apply machine learning algorithms to improve the performance and energy efficiency of mobile devices, like smartphones or IoT devices. For real-time embedded systems, it is about how to schedule real-time applications, such as autonomous driving tasks, on embedded GPUs to meet real-time deadlines.
"The constraints on AI compute are very predictable...... A year ago, the shortage was chips......Then, the next shortage will be electricity. They won't be able to find enough electricity to run all the chips. I think next year, you'll see they just can't find enough electricity to run all the chips." said Elon Musk in March 2024.
Interested students please directly contact the professor as early as possible for full consideration of the GRA positions.
u.osu.edu
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