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1. Adaptive HPC Input/Output Systems

2. Effects of Parallel and Distributed Learning on CNN Performance for Lung Disease Classification

3. Malleable and Adaptive Ad-Hoc File System for Data Intensive Workloads in HPC Applications

4. Malleable Techniques and Resource Scheduling to Improve Energy Efficiency in Parallel Applications

5. Hercules: Scalable and Network Portable In-Memory Ad-Hoc File System for Data-Centric and High-Performance Applications

6. Novel Deep Learning-Based Technique for Tuberculosis Bacilli Detection in Sputum Microscopy

7. A parallel-computing algorithm for high-energy physics particle tracking and decoding using GPU architectures

8. IMSS: In-Memory Storage System for Data Intensive Applications

10. A Novel Data-Centric Programming Model for Large-Scale Parallel Systems

12. Cache-Aware Roofline Model and Medical Image Processing Optimizations in GPUs

13. I/O-Focused Cost Model for the Exploitation of Public Cloud Resources in Data-Intensive Workflows

16. A Data-Aware Scheduling Strategy for DMCF workflows over Hercules

18. Work in progress about enhancing the programmability and energy efficiency of storage in HPC and cloud environments

19. A generic I/O architecture for data-intensiveapplications based on in-memorydistributed cache

20. Exploiting data locality in Swift/T workflows using Hercules

21. Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016)

22. Evaluating data caching techniques in DMCF workflows using Hercules

23. Optimizing Federated Learning Using Remote Embeddings for Graph Neural Networks

24. Asymmetric Coded Distributed Computation for Resilient Prediction Serving Systems

25. Inference with Transformer Encoders on ARM and RISC-V Multicore Processors

26. Improving Generalization and Personalization in Long-Tailed Federated Learning via Classifier Retraining

27. LogRCA: Log-Based Root Cause Analysis for Distributed Services

28. WActiGrad: Structured Pruning for Efficient Finetuning and Inference of Large Language Models on AI Accelerators

29. GDL-GNN: Applying GPU Dataloading of Large Datasets for Graph Neural Network Inference

30. PEANUTS: A Persistent Memory-Based Network Unilateral Transfer System for Enhanced MPI-IO Data Transfer

31. FLUK: Protecting Federated Learning Against Malicious Clients for Internet of Vehicles

32. FedGG: Leveraging Generative Adversarial Networks and Gradient Smoothing for Privacy Protection in Federated Learning

33. VeriChroma: Ownership Verification for Federated Models via RGB Filters

34. Quartet: A Holistic Hybrid Parallel Framework for Training Large Language Models

35. Combining Compression and Prefetching to Improve Checkpointing for Inverse Seismic Problems in GPUs

36. CSIMD: Cross-Search Algorithm with Improved Multi-dimensional Dichotomy for Micro-Batch-Based Pipeline Parallel Training in DNN

37. Disttack: Graph Adversarial Attacks Toward Distributed GNN Training

38. Optimizing Communication for Latency Sensitive HPC Applications on up to 48 FPGAs Using ACCL

39. Lightweight Byzantine-Robust and Privacy-Preserving Federated Learning

40. Athena: Add More Intelligence to RMT-Based Network Data Plane with Low-Bit Quantization

41. Fault Tolerant in the Expand Ad-Hoc Parallel File System

42. ImSPU: Implicit Sharing of Computation Resources Between Vector and Scalar Processing Units

43. FakeGuard: Novel Architecture Support for Deepfake Detection Networks

44. Watt: A Write-Optimized RRAM-Based Accelerator for Attention

45. Exploring Processor Micro-architectures Optimised for BLAS3 Micro-kernels

46. ADE-HGNN: Accelerating HGNNs Through Attention Disparity Exploitation

47. Parallel Writing of Nested Data in Columnar Formats

48. Compact Parallel Hash Tables on the GPU

49. Hybrid Congestion Control for BXI-Based Interconnection Networks

50. MEPAD: A Memory-Efficient Parallelized Direct Convolution Algorithm for Deep Neural Networks

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