An online heuristic for data placement in computer systems with active disks
Sumalatha Adabala, J.A.B. Fortes
Abstract
Sumalatha Adabala, J.A.B. Fortes
Abstract
In this paper, an online heuristic is proposed and evaluated, for managing the dynamic memory in a computer system with active disks, by physically colocating in disk memory or main memory, the data pages being accessed by a computation slice. This enables a runtime system that can offload the corresponding computation slice to the appropriate processing unit at the disk memory or main memory. A modified version of SEQUITUR, an online compression algorithm, is used to identify the affinity among sets of pages in a virtual memory page reference stream, and a page allocation and replacement policy is presented. The sets of pages identified are shown to closely match the sets of pages referenced by computation slices, using a suite of data access kernels as benchmarks. The paging policy is evaluated with page traces of micro benchmarks and real applications. In memory constrained environments, with additional memory at the disk, most of the benchmarks see improved performance, due to fewer page faults. The paging heuristic can colocate 50% of the affinity sets on average and can offload up to 100% of the computation to disk.
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In this paper, an online heuristic is proposed and evaluated, for managing the dynamic memory in a computer system with active disks, by physically colocating in disk memory or main memory, the data pages being accessed by a computation slice. This enables a runtime system that can offload the corresponding computation slice to the appropriate processing unit at the disk memory or main memory. A modified version of SEQUITUR, an online compression algorithm, is used to identify the affinity among sets of pages in a virtual memory page reference stream, and a page allocation and replacement policy is presented. The sets of pages identified are shown to closely match the sets of pages referenced by computation slices, using a suite of data access kernels as benchmarks. The paging policy is evaluated with page traces of micro benchmarks and real applications. In memory constrained environments, with additional memory at the disk, most of the benchmarks see improved performance, due to fewer page faults. The paging heuristic can colocate 50% of the affinity sets on average and can offload up to 100% of the computation to disk.
Key concepts: Demand paging, Page fault, Computer science, Paging, Virtual memory, Memory map, Page, Computation