The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: Fourth Workshop on Heterogeneous Memory Systems (HMEM)
Authors: Mark Hildebrand, Jason Lowe-Power, and Venkatesh Akella (University of California, Davis)
Abstract: We 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.
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