Publication

Chiplet Technology and Systems of Integrated Chips

Y. Yang, Y. Wang, T. Yi, C. Chen, Q Liu, “A 6.4-Gbps 0.41-pJ/b fully-digital die-to-die interconnect PHY for silicon interposer based 2.5D integration”, Integration VLSI, Volume 96, 2024.
C. Chen et al., “Design Challenges of Intrachiplet and Interchiplet Interconnection,” in IEEE Design & Test, vol. 39, no. 6, pp. 99-109, Dec. 2022
J. Liao , …, C. Chen, “A Scalable Die-to-Die Interconnect with Replay and Repair Schemes for 2.5D/3D Integration,” ISCAS 2023.

In-memory Computing Macros and Chips

H. Zhu, …, and C. Chen, “Trident-CIM: A LUT-Based Compute-in-Memory Macro With Trident Read Bit-Line and Partial Product Pruning,” in IEEE TCAS-II.(Early Access)
S. Liu, …, C. Chen, “HARDSEA: Hybrid Analog-ReRAM Clustering and Digital-SRAM In-Memory Computing Accelerator for Dynamic Sparse Self-Attention in Transformer,” in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 32, no. 2, pp. 269-282, Feb. 2024. (Corresponding Author)
S. Liu, …, C. Chen, Q. Liu, M. Liu, “A 28nm 53.8TOPS/W 8b Sparse Transformer Accelerator with In-Memory Butterfly Zero Skipper for Unstructured-Pruned NN and CIM-Based Local-Attention-Reusable Engine,” ISSCC 2023. (Corresponding Author)
H. Zhu, …, C. Chen, …, M. Liu, “COMB-MCM: Computing-on-Memory-Boundary NN Processor with Bipolar Bitwise Sparsity Optimization for Scalable Multi-Chiplet- Module Edge Machine Learning,” ISSCC 2022. (Corresponding Author)
C. Mu …, C. Chen, Q. Liu, “A 200M-Query-Vector/s Computing-in-RRAM ADC-less k-Nearest-Neighbor Accelerator with Time-Domain Winner-Takes-All Circuits,” AICAS 2022, Incheon, Korea. (Corresponding Author)
K. Zhou …, C. Chen, …, M. Liu, “A 28 nm 81 Kb 59–95.3 TOPS/W 4T2R ReRAM Computing-in-Memory Accelerator With Voltage-to-Time-to-Digital Based Output,” IEEE JETCAS, vol. 12, no. 4, pp. 846-857, Dec. 2022.
S. Liu, H. Zhu, C. Chen, L. Zhang and C. -J. Richard Shi, “XNORAM: An Efficient Computing-in-Memory Architecture for Binary Convolutional Neural Networks with Flexible Dataflow Mapping,” 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), Genova, Italy, 2020, pp. 21-25. (Corresponding Author)
H. Zhu, C. Chen, et al., “A Communication-Aware DNN Accelerator on ImageNet Using in-Memory Entry-Counting Based Algorithm-Circuit-Architecture Co-Design in 65nm CMOS,” in IEEE Journal on Emerging and Selected Topics in Circuits and System. (Corresponding Author)

Deep Learning Processor

J. Zheng, …, C. Chen and Q. Liu, “TiPU: A Spatial-Locality-Aware Near-Memory Tile Processing Unit for 3D Point Cloud Neural Network,” DAC 2023. (Corresponding Author)
H. Jiang , …, C. Chen and Q. Liu, “A 2.53μW/channel Event-Driven Neural Spike Sorting Processor with Sparsity-Aware Computing-In-Memory Macros,” ISCAS 2023. (Corresponding Author)
C. Chen, X. Liu, H. Peng, H. Ding and C. -. Richard Shi, “iFPNA: A Flexible and Efficient Deep Learning Processor in 28-nm CMOS Using a Domain-Specific Instruction Set and Reconfigurable Fabric,” in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 9, no. 2, pp. 346-357, June 2019.
C. Chen, et al., “Exploring the Programmability for Deep Learning Processors: from Architecture to Tensorization,” 2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC), San Francisco, CA, 2018, pp. 1-6.
C. Chen, et al., “iFPNA: A Flexible and Efficient Deep Neural Network Accelerator with a Programmable Data Flow Engine in 28nm CMOS,” ESSCIRC 2018 - IEEE 44th European Solid State Circuits Conference (ESSCIRC), Dresden, 2018, pp. 170-173.
C. Chen, et al., “OCEAN: An On-Chip Incremental-Learning Enhanced Artificial Neural Network Processor With Multiple Gated-Recurrent-Unit Accelerators,” in IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 8, no. 3, pp. 519-530, Sept. 2018.
C. Chen, et al., “OCEAN: An on-chip incremental-learning enhanced processor with gated recurrent neural network accelerators,” ESSCIRC 2017 - 43rd IEEE European Solid State Circuits Conference, Leuven, 2017, pp. 259-262.

Mixed Signal Circuit and System Design (for ADCs and Sensors)

W. Jiang, Y. Zhu, C. Chen, et al., “A 14b 500 MS/s Single-Channel Pipelined-SAR ADC With Reference Ripple Mitigation Techniques and Adaptively Biased Floating Inverter Amplifier,” in IEEE Journal of Solid-State Circuits, vol. 58, no. 10, pp. 2709-2721, Oct. 2023
D. Zhai …, C. Chen, “High-Speed and Time-Interleaved ADCs Using Additive-Neural-Network-Based Calibration for Nonlinear Amplitude and Phase Distortion,” IEEE TCAS-I, vol. 69, no. 12, pp. 4944-4957, Dec. 2022.
T. Zhang, Y. Cao, S. Zhang, C. Chen, F. Ye and J. Ren, “Machine Learning Based Prior-Knowledge-Free Calibration for Split Pipelined-SAR ADCs with Open-Loop Amplifiers Achieving 93.7-dB SFDR”, ESSCIRC 2019, Krakow pp.189-192. (speaker, co-corresponding author)
A. Wang, C. Chen, C. Liu and C. R. Shi, “A 9-bit Resistor-Based Highly-Digital Temperature Sensor with a SAR-Quantization Embedded Differential Low-Pass Filter in 65nm CMOS with a 2.5μs Conversion Time,” in IEEE Sensors Journal.
A. Wang, C. Chen and C. R. Shi, “A 9-bit Resistor-Based All-Digital Temperature Sensor with a SAR-Quantization Embedded Differential Low-Pass Filter in 65nm CMOS Consuming 57pJ with a 2.5 $\mu$s Conversion Time”, ICC 2019, Austin TX, April 2019.
A. Wang, C. Chen and C. R. Shi, “Design and Analysis of an Always-ON Input-Biased pA-Current Sub-nW mV-Threshold Hysteretic Comparator for Near-Zero Energy Sensing,” in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 64, no. 9, pp. 2284-2294, Sept. 2017.
C. Chen, et al., “An ARMA-Model-Based NTF Estimation on Continuous-Time$\Delta\Sigma$Modulators,” in IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 62, no. 8, pp. 721-725, Aug. 2015.
C. Chen, et al., “A low-offset calibration-free comparator with a mismatch-suppressed dynamic preamplifier,” 2014 IEEE International Symposium on Circuits and Systems (ISCAS), Melbourne VIC, 2014, pp. 2361-2364.
C. Chen, et al., “An 8-bit 100-MS/s Digital-to-Skew Converter with 200-ps range for time-interleaved sampling,” 2012 IEEE 55th International Midwest Symposium on Circuits and Systems (MWSCAS), Boise, ID, 2012, pp. 1100-1103.
B. Yu, C. Chen, et al., “A 14-bit 200-MS/s time-interleaved ADC with sample-time error detection and cancelation,” IEEE Asian Solid-State Circuits Conference 2011, Jeju, 2011, pp. 349-352.

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