Xi Chen

Orcid: 0009-0009-0119-5966

Affiliations:
  • Southeast University, Nanjing, China


According to our database1, Xi Chen authored at least 17 papers between 2017 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
A 28-nm 16-kb Aggregation and Combination Computing-in-Memory Macro With Dual-Level Sparsity Modulation and Sparse-Tracking ADCs for GCNs.
IEEE J. Solid State Circuits, March, 2025

14.7 NeuroPilot: A 28nm, 69.4fJ/node and 0.22ns/node, 32×32 Mimetic-Path-Searching CIM-Macro with Dynamic-Logic Pilot PE and Dual-Direction Searching.
Proceedings of the IEEE International Solid-State Circuits Conference, 2025

14.6 A 28nm 64kb Bit-Rotated Hybrid-CIM Macro with an Embedded Sign-Bit-Processing Array and a Multi-Bit-Fusion Dual-Granularity Cooperative Quantizer.
Proceedings of the IEEE International Solid-State Circuits Conference, 2025

Modeling of Less-Significant Group Quantization for Hybrid CIM Architecture.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2025

AIM: Software and Hardware Co-design for Architecture-level IR-drop Mitigation in High-performance PIM.
Proceedings of the 52nd Annual International Symposium on Computer Architecture, 2025

TRIFP-DCIM: A Toggle-Rate-Immune Floating-point Digital Compute-in-Memory Design with Adaptive-Asymmetric Compute-Tree.
Proceedings of the 30th Asia and South Pacific Design Automation Conference, 2025

2024
Toggle Rate Aware Quantization Model Based on Digital Floating-Point Computing-In-Memory Architecture.
IEEE Trans. Circuits Syst. II Express Briefs, June, 2024

34.3 A 22nm 64kb Lightning-Like Hybrid Computing-in-Memory Macro with a Compressed Adder Tree and Analog-Storage Quantizers for Transformer and CNNs.
Proceedings of the IEEE International Solid-State Circuits Conference, 2024

A 28nm 16kb Aggregation and Combination Computing-in-Memory Macro with Dual-level Sparsity Modulation and Sparse-Tracking ADCs for GCNs.
Proceedings of the IEEE Custom Integrated Circuits Conference, 2024

2023
From macro to microarchitecture: reviews and trends of SRAM-based compute-in-memory circuits.
Sci. China Inf. Sci., October, 2023

Evaluation Platform of Time-Domain Computing-in-Memory Circuits.
IEEE Trans. Circuits Syst. II Express Briefs, March, 2023

Evaluation Model for Current-Domain SRAM-based Computing-in-Memory Circuits.
Proceedings of the 16th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2023

A 28nm 64-kb 31.6-TFLOPS/W Digital-Domain Floating-Point-Computing-Unit and Double-Bit 6T-SRAM Computing-in-Memory Macro for Floating-Point CNNs.
Proceedings of the IEEE International Solid- State Circuits Conference, 2023

2022
VCCIM: a voltage coupling based computing-in-memory architecture in 28 nm for edge AI applications.
CCF Trans. High Perform. Comput., December, 2022

A Quantization Model Based on a Floating-point Computing-in-Memory Architecture.
Proceedings of the IEEE Asia Pacific Conference on Circuit and Systems, 2022

2017
FxpNet: Training a deep convolutional neural network in fixed-point representation.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

FP-DNN: An Automated Framework for Mapping Deep Neural Networks onto FPGAs with RTL-HLS Hybrid Templates.
Proceedings of the 25th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2017


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