Publication | Closed Access
PIMCA: A 3.4-Mb Programmable In-Memory Computing Accelerator in 28nm for On-Chip DNN Inference
36
Citations
0
References
2021
Year
Unknown Venue
Electrical EngineeringOn-chip Dnn InferenceEngineeringCustom IsaHardware AccelerationHigh-performance ArchitectureComputer EngineeringComputer ArchitectureDomain-specific AcceleratorComputer ScienceParallel ComputingDeep LearningMicroelectronicsDeep Neural NetworkMemory ArchitectureIn-memory ComputingLargest Imc Hardware
We present a programmable in-memory computing (IMC) accelerator integrating 108 capacitive-coupling-based IMC SRAM macros of a total size of 3.4 Mb, demonstrating one of the largest IMC hardware to date. We developed a custom ISA featuring IMC and SIMD functional units with hardware loop to support a range of deep neural network (DNN) layer types. The 28nm prototype chip achieves system-level peak energy-efficiency of 437 TOPS/W and peak throughput of 4.9 TOPS at 40MHz, 1V supply.