Tobias Scheuer

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Task scheduling typically employs a worker thread per hardware context to process a dynamically changing set of tasks. It is an appealing solution to exploit modern multi-core processors, as it eases parallelization and avoids unnecessary context switches and their associated costs. Näıvely bundling DBMS operations into tasks, however, can result in(More)
Non-uniform memory access (NUMA) architectures pose numerous performance challenges for main-memory column-stores in scaling up analytics on modern multi-socket multi-core servers. A NUMAaware execution engine needs a strategy for data placement and task scheduling that prefers fast local memory accesses over remote memory accesses, and avoids an imbalance(More)
Main-memory column-stores are called to efficiently use modern non-uniform memory access (NUMA) architectures to service concurrent clients on big data. The efficient usage of NUMA architectures depends on the data placement and scheduling strategy of the column-store. Most column-stores choose a static strategy that involves partitioning all data across(More)
Today’s hardware architectures provide an ever-increasing number of CPU cores that can be used for running concurrent operations. A big challenge is to ensure that these operations are properly synchronized and make efficient use of the available resources. Fellow database researchers have appropriately described this problem as “staring into the abyss” of(More)
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