Publication | Closed Access
Serving DNNs in Real Time at Datacenter Scale with Project Brainwave
333
Citations
9
References
2018
Year
EngineeringHigh Performance Computer NetworkAdvanced ComputingComputer ArchitectureData Center NetworkData ScienceHigh-performance ArchitectureComputing SystemsEmbedded Machine LearningParallel ComputingDatacenter ScaleData Center SystemComputer EngineeringComputer ScienceDeep LearningNeural Architecture SearchDeep Neural NetworkProject BrainwaveHardware AccelerationEdge ComputingParallel ProgrammingReal Time
To meet the computational demands required of deep learning, cloud operators are turning toward specialized hardware for improved efficiency and performance. Project Brainwave, Microsofts principal infrastructure for AI serving in real time, accelerates deep neural network (DNN) inferencing in major services such as Bings intelligent search features and Azure. Exploiting distributed model parallelism and pinning over low-latency hardware microservices, Project Brainwave serves state-of-the-art, pre-trained DNN models with high efficiencies at low batch sizes. A high-performance, precision-adaptable FPGA soft processor is at the heart of the system, achieving up to 39.5 teraflops (Tflops) of effective performance at Batch 1 on a state-of-the-art Intel Stratix 10 FPGA.
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