Euro-Par 2024: Parallel Processing Workshops Euro-Par 2024 International Workshops, Madrid, Spain, August 26–30, 2024, Proceedings, Part I /
The two-volume set LNCS 15385 + 15386 constitutes the proceedings of the workshops and associated events that were held in conjunction with the 30th European Conference on Parallel and Distributed Processing, Euro-Par 2024, which took place in Madrid, Spain, during August 26–30, 2024. Overall, the E...
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| Altres autors: | , , , , , , , , , , , , , , , |
| Format: | Electrònic eBook |
| Idioma: | anglès |
| Publicat: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Edició: | 1st ed. 2025. |
| Col·lecció: | Lecture Notes in Computer Science,
15385 |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1007/978-3-031-90200-0 |
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Taula de continguts:
- Preface of the European Workshop on Quantum Computing for High-Performance Computing
- Hybrid Quantum Computing: the Use Case of Shor's Algorithm
- A Quantum Emulation Workbench for Benchmark Construction and Application Development
- TNBS: A Kernel-Based Benchmarking for Digital Quantum Computers
- Variational Quantum Eigensolver for Classification in Distributed Data Sets
- LazyQML: A Python library to benchmark Quantum Machine Learning models
- Optimizing a quantum BCD Adder in terms of T-gates and CNOT gates
- Factoring integers via Schnorr's algorithm assisted with VQE
- Adiabatic training for Variational Quantum Algorithms
- Quantum Compilation Process: a Survey
- 19th International Workshop on Virtualization in High-Performance Cloud Computing (VHPC 2024)
- An Investigation of the Linux Virtual Networking Latencies
- Performance Implications of SEV Virtual Machine Live Migration
- Boosting Serverless Computing: A Survey on Architecture Designs and Accelerator Support for Serverless Platforms
- LLMs for Virtualized Networking Infrastructures: An Industrial Report
- Towards Using Partitioned GPU Virtual Functions for Mixture of Experts
- International Workshop in High-Performance Computing in Physics (PHYSHPC)
- Runtime Instantiation of Kernels for Fast Fourier Transforms Using SYCL Specialization Constants
- Towards Large-scale Top-Down Microarchitecture Analysis Using the Score-P Framework
- Coalescing MPI communication in 6D Vlasov simulations: solving ghost domains in Vlasiator
- Understanding the Impact of openPMD on BIT1, a Particle-in-Cell Monte Carlo Code, through Instrumentation, Monitoring, and In-Situ Analysis
- Workshop proceedings
- Lessons Learned and Scalability Achieved When Porting Uintah to DOE Exascale Systems
- Evaluating AI-generated code for C++, Fortran, Go, Java, Julia, Matlab, Python, R, and Rust
- Investigating the Performance Difference of Task Communication via Futures or Side Effects
- GVEL: Fast Graph Loading in Edgelist and Compressed Sparse Row (CSR) formats
- Workshop preface
- Dynamic Resource Manager for Automating Deployments in the Computing Continuum
- Parallel Efficiency-aware Standard MPI-based Malleability
- The Impact of Evolving APGAS Programs on HPC Clusters
- Malleability in the Expand Ad-Hoc parallel file system
- Evaluation of a Dynamic Resource Management Strategy for Elastic Scientific Workflows
- MaM: A User-Friendly Interface to Incorporate Malleability into MPI Applications
- Towards a Scale Invariant Syntax for Dynamic Job-Level Workflows
- 22nd International Workshop on Algorithms, Models, and Tools for Parallel Computing on Heterogeneous Platforms (HeteroPar 2024)
- StarONNX: a Scheduler for Efficient Inference on Heterogeneous Resources
- Strategies for memory management improvement in deep learning algorithms for contrast enhancement of high-resolution radiological images
- Computing DTWs on CPU, GPU and FPGA with SYCL
- Challenging Portability Paradigms: FPGA Acceleration Using SYCL and OpenCL
- A Practical Survey on Static Task Scheduling Optimization Approaches for Heterogeneous Architectures
- Element scheduling for GPU-accelerated finite-volumes computations
- Containerization for Heterogeneous and Hybrid Parallelism
- A Chapel-based Multi-GPU Branch-and-Bound Algorithm
- Accelerating Scientific Computing Kernels by Fusing the Polyhedral and Tensor Compilers
- Exploring the Limits of Cross-Platform Sparse Tensor Processing.