Latest Research in Parallel Computing and Optimization Techniques

Top Research Topics in Parallel Computing and Optimization Techniques

• Hardware Architecture — 12 papers
• Parallel Computing and Optimization Techniques — 7 papers
• Machine Learning — 5 papers
• Information Theory — 5 papers
• Distributed, Parallel, and Cluster Computing — 4 papers
• Image and Video Processing — 4 papers
• Wireless Signal Modulation Classification — 2 papers
• Signal Processing — 2 papers
• Systems and Control — 2 papers
• Computer Vision and Pattern Recognition — 2 papers

Highest-Cited Papers

1. Machine-Learned Mismatch and Task Preservation Beliefs in CoSMA DAI for Common Knowledge Aware Semantic Alignment
2. ADEM: Accelerating Sparse Matrix Multiplication with Adaptive Dataflow and Efficient Merging
3. RISC-V and machine learning: a survey
4. Quantifying the Effect of HCLs on a Fixed-Microarchitecture MXFP4 Accelerator
5. SemISAC: Semantic Integrated Sensing and Communications
6. NeuroFlex: Lossless Element-Level ANN-SNN Co-Execution for Efficient Sparse Inference
7. Carry-Through Checksum: A Lightweight Fault-Detection for CNN Inference at the Edge
8. Is INT8 Portable? A Cross-Platform Measurement Study of Quantized Inference on Embedded and Automotive Accelerators
9. Deep Neural Networks for Real-Time Medical Streaming in 6G Cross-Modal Semantic Communication Systems
10. Hardware-Aware Acceleration of Open-Vocabulary Multi-Object Navigation on Edge GPUs
11. PEAT: Pseudo-Error Assessment for GPU Kernel Validation in DNN Training
12. Active Filter Design for Buffering Datacenter-Scale Power Fluctuations from Training AI
13. Fengshui: Demystifying Chiplet Ecosystem and Bespoke Neural Network Accelerator Codesign
14. SparseDitto: An Agentic Sparse Compilation Framework through Architecture-Aware Synthesis on GPUs
15. AccelForge: Comprehensive Modeling and Co-Design Framework for AI Accelerators
16. When Does Low-Bit Quantization Preserve the Decisions of Vector Search?
17. Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation
18. Take What You Need: Flexible Multi-Task Semantic Communications with Channel Adaptation
19. On Generalisation Error Bounds for Transformers
20. Approximately Optimal Multi-Stream Quickest Change Detection