2019 · 48 citations · 26 references
ComputingComputer EngineeringComputer ScienceComputer ArchitectureMachine LearningMemoryAccelerator ArchitectureAccelerator IntegrationDeep LearningHardware AccelerationMemory Hierarchy OptimizationMemory Subsystem DesignAcceleratorsBandwidthBandwidth OverheadComplex MultiplicationConvolutional Neural NetworksDeep Learning AccelerationDeep Learning AcceleratorsMemory Bandwidth Optimization
PIM (Processing-in-memory)-based CNN (Convolutional neural network) accelerators leverage the characteristics of basic memory cells to enable simple logic and arithmetic operations so that the bandwidth constraint can be effectively alleviated. However, it remains a major challenge to support multiplication operations efficiently on PIM accelerators, in particular, DRAM-based PIM accelerators. This has prevented PIM-based accelerators from being immediately adopted for accurate CNN inference.
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