Publication | Closed Access
MemcachedGPU
55
Citations
45
References
2015
Year
Unknown Venue
Workload ConsolidationCluster ComputingData Center ManagementEngineeringData Center SystemEdge ComputingCloud ComputingComputer EngineeringComputer ArchitectureDatacenter-scale ComputingData CentersParallel ProgrammingLow LatencyData Center NetworkLatency BandwidthParallel ComputingScalable Computing
This paper tackles the challenges of obtaining more efficient data center computing while maintaining low latency, low cost, programmability, and the potential for workload consolidation. We introduce GNoM, a software framework enabling energy-efficient, latency bandwidth optimized UDP network and application processing on GPUs. GNoM handles the data movement and task management to facilitate the development of high-throughput UDP network services on GPUs. We use GNoM to develop MemcachedGPU, an accelerated key-value store, and evaluate the full system on contemporary hardware.
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