Conferences · eligible papers
ICCAD
2021–2025 確定版
2023 · 172 papers
このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。
- Meltrix: A RRAM-Based Polymorphic Architecture Enhanced by Function Synthesis
日本大学: 関与なし(対象大学)
- Memory-aware Scheduling for Complex Wired Networks with Iterative Graph Optimization
日本大学: 関与なし(対象大学)
- MiniTNtk: An Exact Synthesis-based Method for Minimizing Transistor Network
日本大学: 関与なし(対象大学)
- MirrorNet: A TEE-Friendly Framework for Secure On-Device DNN Inference
日本大学: 関与なし(対象大学)
- Monad: Towards Cost-Effective Specialization for Chiplet-Based Spatial Accelerators
日本大学: 関与なし(対象大学)
- Multi-Objective Architecture Search and Optimization for Heterogeneous Neuromorphic Architecture
日本大学: 関与なし(対象大学)
- Multi-Product Optimization for 3D Heterogeneous Integration with D2W Bonding
日本大学: 関与なし(対象大学)
- Multi-Task Evolutionary to PVT Knowledge Transfer for Analog Integrated Circuit Optimization
日本大学: 関与なし(対象大学)
- NearUni: Near-Unitary Training for Efficient Optical Neural Networks
日本大学: 関与なし(対象大学)
- NeuroEscape: Ordered Escape Routing via Monte-Carlo Tree Search and Neural Network
日本大学: 関与なし(対象大学)
- OPT: Optimal Proposal Transfer for Efficient Yield Optimization for Analog and SRAM Circuits
日本大学: 関与なし(対象大学)
- One-Dimensional Deep Image Prior for Curve Fitting of S-Parameters from Electromagnetic Solvers
日本大学: 関与なし(対象大学)
- Optimal Layout Synthesis for Quantum Circuits as Classical Planning
日本大学: 関与なし(対象大学)
- Optimizing LUT-Based Quantum Circuit Synthesis Using Relative Phase Boolean Operations
日本大学: 立命館大学
- PANDA: Architecture-Level Power Evaluation by Unifying Analytical and Machine Learning Solutions
日本大学: 関与なし(対象大学)
- PBA: Percentile-Based Level Allocation for Multiple-Bits-Per-Cell RRAM
日本大学: 関与なし(対象大学)
- PDNSig: Identifying Multi-Tenant Cloud FPGAs with Power Distribution Network-Based Signatures
日本大学: 関与なし(対象大学)
- PP-Transformer: Enable Efficient Deployment of Transformers Through Pattern Pruning
日本大学: 関与なし(対象大学)
- PRIMO: A Full-Stack Processing-in-DRAM Emulation Framework for Machine Learning Workloads
日本大学: 関与なし(対象大学)
- PSOFuzz: Fuzzing Processors with Particle Swarm Optimization
日本大学: 関与なし(対象大学)
- Path-Based Processing using In-Memory Systolic Arrays for Accelerating Data-Intensive Applications
日本大学: 関与なし(対象大学)
- PostPINN-EM: Fast Post-Voiding Electromigration Analysis Using Two-Stage Physics-Informed Neural Networks
日本大学: 関与なし(対象大学)
- Power Distribution Network Optimization Using HLA-GCN for Routability Enhancement
日本大学: 関与なし(対象大学)
- Power-Aware Training for Energy-Efficient Printed Neuromorphic Circuits
日本大学: 関与なし(対象大学)
- Practical Layout-Aware Analog/Mixed-Signal Design Automation with Bayesian Neural Networks
日本大学: 関与なし(対象大学)
- Protection Against Physical Attacks Through Self-Destructive Polymorphic Latch
日本大学: 関与なし(対象大学)
- QPulseLib: Accelerating the Pulse Generation of Quantum Circuit with Reusable Patterns
日本大学: 関与なし(対象大学)
- READ: Reliability-Enhanced Accelerator Dataflow Optimization Using Critical Input Pattern Reduction
日本大学: 関与なし(対象大学)
- RNA-ViT: Reduced-Dimension Approximate Normalized Attention Vision Transformers for Latency Efficient Private Inference
日本大学: 関与なし(対象大学)
- RONet: Scaling GPU System with Silicon Photonic Chiplet
日本大学: 関与なし(対象大学)
- Rapid-INR: Storage Efficient CPU-Free DNN Training Using Implicit Neural Representation
日本大学: 関与なし(対象大学)
- Real-time Thermal Map Estimation for AMD Multi-Core CPUs Using Transformer
日本大学: 関与なし(対象大学)
- Reflections on Trusting TrustHUB
日本大学: 関与なし(対象大学)
- Reliable Hyperdimensional Reasoning on Unreliable Emerging Technologies
日本大学: 関与なし(対象大学)
- Risk Propagation Based Vector Profiling for High Coverage Dynamic IR-Drop Analysis
日本大学: 関与なし(対象大学)
- Risk-Aware and Explainable Framework for Ensuring Guaranteed Coverage in Evolving Hardware Trojan Detection
日本大学: 関与なし(対象大学)
- Robust GNN-Based Representation Learning for HLS
日本大学: 関与なし(対象大学)
- Routability Prediction and Optimization Using Explainable AI
日本大学: 関与なし(対象大学)
- Routability-Driven Orientation-Aware Analytical Placement for System in Package
日本大学: 関与なし(対象大学)
- Runtime Row/Column Activation Pruning for ReRAM-based Processing-in-Memory DNN Accelerators
日本大学: 関与なし(対象大学)
- SAGA: Sparsity-Agnostic Graph Convolutional Network Acceleration with Near-Optimal Workload Balance
日本大学: 関与なし(対象大学)
- SAM: A Scalable Accelerator for Number Theoretic Transform Using Multi-Dimensional Decomposition
日本大学: 関与なし(対象大学)
- SATformer: Transformer-Based UNSAT Core Learning
日本大学: 関与なし(対象大学)
- SEE-MCAM: Scalable Multi-Bit FeFET Content Addressable Memories for Energy Efficient Associative Search
日本大学: 関与なし(対象大学)
- SOLE: Hardware-Software Co-design of Softmax and LayerNorm for Efficient Transformer Inference
日本大学: 関与なし(対象大学)
- SSDe: FPGA-Based SSD Express Emulation Framework
日本大学: 関与なし(対象大学)
- Secure-by-Construction Design Methodology for CPUs: Implementing Secure Speculation on the RTL
日本大学: 関与なし(対象大学)
- Side Channel-Assisted Inference Attacks on Machine Learning-Based ECG Classification
日本大学: 関与なし(対象大学)
- Single-Qubit Gates Matter for Optimising Quantum Circuit Depth in Qubit Mapping
日本大学: 関与なし(対象大学)
- SpOctA: A 3D Sparse Convolution Accelerator with Octree-Encoding-Based Map Search and Inherent Sparsity-Aware Processing
日本大学: 関与なし(対象大学)
- Spacing Cost-aware Optimal and Efficient Mixed-Cell-Height Detailed Placement for DFM Considerations
日本大学: 関与なし(対象大学)
- Sphinx: A Hybrid Boolean Processor-FPGA Hardware Emulation System
日本大学: 関与なし(対象大学)
- Striving for Both Quality and Speed: Logic Synthesis for Practical Garbled Circuits
日本大学: 関与なし(対象大学)
- Stronger Mixed-Size Placement Backbone Considering Second-Order Information
日本大学: 関与なし(対象大学)
- SurgeFuzz: Surge-Aware Directed Fuzzing for CPU Designs
日本大学: 東京大学
- SystemC Model of Power Side-Channel Attacks Against AI Accelerators: Superstition or not?
日本大学: 関与なし(対象大学)
- Systolic Array Placement on FPGAs
日本大学: 関与なし(対象大学)
- THE-V: Verifiable Privacy-Preserving Neural Network via Trusted Homomorphic Execution
日本大学: 関与なし(対象大学)
- TL-nvSRAM-CIM: Ultra-High-Density Three-Level ReRAM-Assisted Computing-in-nvSRAM with DC-Power Free Restore and Ternary MAC Operations
日本大学: 関与なし(対象大学)
- TRAIN: A Reinforcement Learning Based Timing-Aware Neural Inference on Intermittent Systems
日本大学: 関与なし(対象大学)
- TSTC: Two-Level Sparsity Tensor Core Enabling both Algorithm Flexibility and Hardware Efficiency
日本大学: 関与なし(対象大学)
- TaintFuzzer: SoC Security Verification using Taint Inference-enabled Fuzzing
日本大学: 関与なし(対象大学)
- Technology Mapping Using Multi-Output Library Cells
日本大学: 関与なし(対象大学)
- Thermally-Aware Multi-Core Chiplet Stacking
日本大学: 関与なし(対象大学)
- Towards Effective Training of Robust Spiking Recurrent Neural Networks Under General Input Noise via Provable Analysis
日本大学: 関与なし(対象大学)
- Towards Timing-Driven Routing: An Efficient Learning Based Geometric Approach
日本大学: 関与なし(対象大学)
- VECOM: Variation-Resilient Encoding and Offset Compensation Schemes for Reliable ReRAM-Based DNN Accelerator
日本大学: 関与なし(対象大学)
- VecPAC: A Vectorizable and Precision-Aware CGRA
日本大学: 関与なし(対象大学)
- Verification of Flow-Based Computing Systems Using Bounded Model Checking
日本大学: 関与なし(対象大学)
- WolFEx: Word-Level Function Extraction and Simplification from Gate-Level Arithmetic Circuits
日本大学: 関与なし(対象大学)
- Xel-FPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems
日本大学: 関与なし(対象大学)
- iPL-3D: A Novel Bilevel Programming Model for Die-to-Die Placement
日本大学: 関与なし(対象大学)