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Performance Characterization of Spark Workloads on Shared NUMA Systems., , , and . BigDataService, page 41-48. IEEE Computer Society, (2018)Performance Management of Accelerated MapReduce Workloads in Heterogeneous Clusters., , , , , and . ICPP, page 653-662. IEEE Computer Society, (2010)A highly parameterizable framework for Conditional Restricted Boltzmann Machine based workloads accelerated with FPGAs and OpenCL., , , , , and . Future Generation Comp. Syst., (2020)Accelerating K-mer Frequency Counting with GPU and Non-Volatile Memory., , and . HPCC/SmartCity/DSS, page 434-441. IEEE Computer Society, (2017)Performance-driven task co-scheduling for MapReduce environments., , , , and . NOMS, page 373-380. IEEE, (2010)Performance Evaluation of Microservices Architectures Using Containers., , , , , and . NCA, page 27-34. IEEE Computer Society, (2015)Adaptive MapReduce Scheduling in Shared Environments., , , , , and . CCGRID, page 61-70. IEEE Computer Society, (2014)Considerations in using OpenCL on GPUs and FPGAs for throughput-oriented genomics workloads., , , and . Future Generation Comp. Syst., (2019)Enabling Distributed Key-Value Stores with Low Latency-Impact Snapshot Support., , , , , , and . NCA, page 65-72. IEEE Computer Society, (2013)Topology-aware GPU scheduling for learning workloads in cloud environments., , , , and . SC, page 17:1-17:12. ACM, (2017)