在首尔举办的第31届操作系统原理研讨会上,阿里云推出的Aegaeon计算池化解决方案获大会收录。该研究针对AI模型服务中存在的GPU资源浪费问题,提出了创新性解决路径。目前云服务商普遍面临算力利用失衡的挑战。以阿里云模型市场为例,17.7%的GPU算力仅处理1.35%的请求,资源闲置现象突出。Aegaeon系统通过GPU资源池化技术,实现单个GPU动态服务多个AI模型,成功打破传统绑定模式。经过...
Source Link在首尔举办的第31届操作系统原理研讨会上,阿里云推出的Aegaeon计算池化解决方案获大会收录。该研究针对AI模型服务中存在的GPU资源浪费问题,提出了创新性解决路径。目前云服务商普遍面临算力利用失衡的挑战。以阿里云模型市场为例,17.7%的GPU算力仅处理1.35%的请求,资源闲置现象突出。Aegaeon系统通过GPU资源池化技术,实现单个GPU动态服务多个AI模型,成功打破传统绑定模式。经过...
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