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DHAP: Towards Efficient OLAP in a Disaggregated and Heterogeneous Environment
SessionSystem Software and Cloud
DescriptionDisaggregation of hardware resources and integration of heterogeneous accelerators are two emerging trends in datacenters. Existing data systems focus on either disaggregated systems with CPUs or incorporation of heterogeneous accelerators within traditional monolithic servers. None can adequately address the challenges posed by systems that are both disaggregated and heterogeneous.
We present DHAP, an end-to-end framework comprising a query compiler and a specialized runtime, designed to efficiently process online analytical queries in a disaggregated and heterogeneous environment. At higher levels the compiler, a planning module, automatically identifies efficient execution plans. At lower levels, optimizations are applied to generate executable code for heterogeneous back-ends. The runtime efficiently processes queries on disaggregated CPU/GPU compute nodes, facilitating inter-stage pipelined execution and minimizing communication costs. Experiments show that DHAP achieves near-optimal solutions, with latency speedups of up to 16.3x on SSB and TPC benchmarks. Furthermore, it attains significant speedups compared to existing query processing systems.
We present DHAP, an end-to-end framework comprising a query compiler and a specialized runtime, designed to efficiently process online analytical queries in a disaggregated and heterogeneous environment. At higher levels the compiler, a planning module, automatically identifies efficient execution plans. At lower levels, optimizations are applied to generate executable code for heterogeneous back-ends. The runtime efficiently processes queries on disaggregated CPU/GPU compute nodes, facilitating inter-stage pipelined execution and minimizing communication costs. Experiments show that DHAP achieves near-optimal solutions, with latency speedups of up to 16.3x on SSB and TPC benchmarks. Furthermore, it attains significant speedups compared to existing query processing systems.
Event Type
Paper
TimeThursday, 20 November 20254:15pm - 4:37pm CST
Location275
System Software and Cloud Computing