IEEE Micro

Papers
(The H4-Index of IEEE Micro is 21. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)
ArticleCitations
NVIDIA A100 Tensor Core GPU: Performance and Innovation121
Chipyard: Integrated Design, Simulation, and Implementation Framework for Custom SoCs118
MAESTRO: A Data-Centric Approach to Understand Reuse, Performance, and Hardware Cost of DNN Mappings76
FerroElectronics for Edge Intelligence46
PEFL: Deep Privacy-Encoding-Based Federated Learning Framework for Smart Agriculture45
The Design Process for Google's Training Chips: TPUv2 and TPUv345
Accelerating Genome Analysis: A Primer on an Ongoing Journey42
BlackParrot: An Agile Open-Source RISC-V Multicore for Accelerator SoCs37
FPGA-Based Near-Memory Acceleration of Modern Data-Intensive Applications36
Accelerating Chip Design With Machine Learning31
PyMTL3: A Python Framework for Open-Source Hardware Modeling, Generation, Simulation, and Verification30
MHADBOR: AI-Enabled Administrative-Distance-Based Opportunistic Load Balancing Scheme for an Agriculture Internet of Things Network29
Chasing Carbon: The Elusive Environmental Footprint of Computing29
A Cloud-Optimized Transport Protocol for Elastic and Scalable HPC28
Kunpeng 920: The First 7-nm Chiplet-Based 64-Core ARM SoC for Cloud Services28
Near-Memory Processing in Action: Accelerating Personalized Recommendation With AxDIMM25
Manticore: A 4096-Core RISC-V Chiplet Architecture for Ultraefficient Floating-Point Computing25
OpenFPGA: An Open-Source Framework for Agile Prototyping Customizable FPGAs24
SymbiFlow and VPR: An Open-Source Design Flow for Commercial and Novel FPGAs23
Evolution of the Graphics Processing Unit (GPU)21
ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks21
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