Publication | Closed Access
FPMR
155
Citations
13
References
2010
Year
Cluster ComputingInherent ParallelismEngineeringMachine LearningMapreduce FrameworkComputer ArchitectureParallel ImplementationMap-reduceParallel AlgorithmsData ScienceData MiningParallel ComputingHigh-performance Data AnalyticsComputer EngineeringComputer ScienceParallel ProgrammingData-level ParallelismMassive Data ProcessingBig Data
Machine learning and data mining are gaining increasing attentions of the computing society. FPGA provides a highly parallel, low power, and flexible hardware platform for this domain, while the difficulty of programming FPGA greatly limits its prevalence. MapReduce is a parallel programming framework that could easily utilize inherent parallelism in algorithms. In this paper, we describe FPMR, a MapReduce framework on FPGA, which provides programming abstraction, hardware architecture, and basic building blocks to developers.
| Year | Citations | |
|---|---|---|
Page 1
Page 1