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CachedArrays: API and Framework to Optimize Data Movement for Heterogeneous Memory Systems
DescriptionWe propose a new framework called CachedArrays and a set of APIs to address the data tiering problem in large scale heterogeneous and disaggregated memory systems. The proposed framework operates at a variable size object granularity and allows the programmer to specify semantic hints about future use of data via a Policy API, which are used by a Data Manager to choose when and where to place a particular data object using a data management API, thus bridging the semantic gap between the programmer and the platform-specific hardware details, and optimizing overall performance. We evaluate the proposed framework on a real hardware platform with terabytes of memory consisting of NVRAM and DRAM on large scale ML training workloads such CNNs, DNNs, and DLRM that exhibit different data access and usage patterns.
Event Type
Workshop
TimeFriday, 17 November 202311am - 11:30am MST
Location405-406-407
Data Movement and Memory
Heterogeneous Computing
Programming Frameworks and System Software
W