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ORCID33rd HPDC 2024: Pisa, Italy
- Patrizio Dazzi, Gabriele Mencagli, David K. Lowenthal, Rosa M. Badia:
Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2024, Pisa, Italy, June 3-7, 2024. ACM 2024, ISBN 979-8-4007-0413-0 - Lixian Ma
, Haoruo Chen, En Shao, Leping Wang, Quan Chen, Guangming Tan:
ElasticRoom: Multi-Tenant DNN Inference Engine via Co-design with Resource-constrained Compilation and Strong Priority Scheduling. 1-14 - Yidong Gong, Pradeep Kumar:
GNNOne: A Unified System Optimizations for GNN Kernels. 15-27 - Prithwish Basu, Liangyu Zhao, Jason Fantl, Siddharth Pal, Arvind Krishnamurthy, Joud Khoury:
Efficient all-to-all Collective Communication Schedules for Direct-connect Topologies. 28-41 - Xinning Hui, Yuanchao Xu, Zhishan Guo, Xipeng Shen:
ESG: Pipeline-Conscious Efficient Scheduling of DNN Workflows on Serverless Platforms with Shareable GPUs. 42-55 - Zichao Yang, Hao Guo, Heng Wu, Yuewen Wu, Hua Zhong, Wenbo Zhang, Chuan Zhou, Yan Liu:
ETS: Deep Learning Training Iteration Time Prediction based on Execution Trace Sliding Window. 56-68 - Juneseo Chang, Wanju Doh, Yaebin Moon, Eojin Lee, Jung Ho Ahn:
IDT: Intelligent Data Placement for Multi-tiered Main Memory with Reinforcement Learning. 69-82 - Anh Tran, Ignacio Laguna, Ganesh Gopalakrishnan:
FPBOXer: Efficient Input-Generation for Targeting Floating-Point Exceptions in GPU Programs. 83-93 - Marcin Copik, Alexandru Calotoiu, Pengyu Zhou, Konstantin Taranov, Torsten Hoefler:
FaaSKeeper: Learning from Building Serverless Services with ZooKeeper as an Example. 94-108 - Milan Shah, Xiaodong Yu, Sheng Di, Michela Becchi, Franck Cappello:
A Portable, Fast, DCT-based Compressor for AI Accelerators. 109-121 - Thanh Son Phung, Colin Thomas, Logan T. Ward, Kyle Chard, Douglas Thain:
Accelerating Function-Centric Applications by Discovering, Distributing, and Retaining Reusable Context in Workflow Systems. 122-134 - Zhangqiang Ming, Yuchong Hu, Wenxiang Zhou, Xinjue Zheng, Chenxuan Yao, Dan Feng:
ADTopk: All-Dimension Top-k Compression for High-Performance Data-Parallel DNN Training. 135-147 - Robert Underwood, Meghana Madhyastha, Randal C. Burns, Bogdan Nicolae:
EvoStore: Towards Scalable Storage of Evolving Learning Models. 148-159 - Lei Xu, Haipeng Jia, Yunquan Zhang, Luhan Wang, Xianmeng Jiang:
HAM-SpMSpV: an Optimized Parallel Algorithm for Masked Sparse Matrix-Sparse Vector Multiplications on multi-core CPUs. 160-173 - Yongshu Bai, Zhihui Yang, Feng Gao:
Faast: An Efficient Serverless Framework Made Snapshot-based Function Response Fast. 174-185 - Antonios Katsarakis, Vasilis Gavrielatos, Nikos Ntarmos:
DLHT: A Non-blocking Resizable Hashtable with Fast Deletes and Memory-awareness. 186-199 - Sergi Laut, Ricard Borrell, Marc Casas:
Extending Sparse Patterns to Improve Inverse Preconditioning on GPU Architectures. 200-213 - Christos Katsakioris, Chloe Alverti, Konstantinos Nikas, Dimitrios Siakavaras, Stratos Psomadakis, Nectarios Koziris:
FaaSRail: Employing Real Workloads to Generate Representative Load for Serverless Research. 214-226 - Avinash Maurya, Robert Underwood, M. Mustafa Rafique, Franck Cappello, Bogdan Nicolae:
DataStates-LLM: Lazy Asynchronous Checkpointing for Large Language Models. 227-239 - Isaac Boixaderas, Sergi Moré, Javier Bartolome, David Vicente, Petar Radojkovic, Paul M. Carpenter, Eduard Ayguadé:
Reinforcement Learning-based Adaptive Mitigation of Uncorrected DRAM Errors in the Field. 240-252 - Sunyeol Hwang, Eungyeong Lee, Hongseok Oh, Youngmin Yi:
FASOP: Fast yet Accurate Automated Search for Optimal Parallelization of Transformers on Heterogeneous GPU Clusters. 253-266 - Sohaib Ahmad, Hui Guan, Ramesh K. Sitaraman:
Loki: A System for Serving ML Inference Pipelines with Hardware and Accuracy Scaling. 267-280 - Daniel Nichols, Joshua Hoke Davis, Zhaojun Xie, Arjun Rajaram, Abhinav Bhatele:
Can Large Language Models Write Parallel Code? 281-294 - Mansub Song, Lan Anh Nguyen, Sunggon Kim, Hyeonsang Eom, Yongseok Son:
ScaleDFS: Accelerating Decentralized and Private File Sharing via Scaling Directed Acyclic Graph Processing. 295-308 - Shihui Song, Yafan Huang, Peng Jiang, Xiaodong Yu, Weijian Zheng, Sheng Di, Qinglei Cao, Yunhe Feng, Zhen Xie, Franck Cappello:
CereSZ: Enabling and Scaling Error-bounded Lossy Compression on Cerebras CS-2. 309-321 - Kirtus G. Leyba, Steven A. Hofmeyr, Stephanie Forrest, Judy L. Cannon, Melanie E. Moses:
SIMCoV-GPU: Accelerating an Agent-Based Model for Exascale. 322-333 - Piotr Luczynski, Lukas Gianinazzi, Patrick Iff, Leighton Wilson, Daniele De Sensi, Torsten Hoefler:
Near-Optimal Wafer-Scale Reduce. 334-347 - Claudio Cicconetti:
A Practical Introduction to Quantum Computing and Networking. 348-349 - Carlo Mastroianni, Andrea Vinci:
Tutorial on Variational Quantum Algorithms for Resource Management in Cloud/Edge Architectures. 350-351 - Domenico Talia, Paolo Trunfio:
Programming Tools for High-Performance Data Analysis. 352-355 - Engin Zeydan, Josep Mangues, Jorge Baranda:
Network Management and Orchestration with Data Engineering: A Practical Guide. 356-357 - Marta Jaros, Jirí Jaros:
k-Dispatch: Enabling Cost-Optimized Biomedical Workflow Offloading. 358-360 - Ondrej Olsak, Jirí Jaros:
Techniques for Efficient Fourier Transform Computation in Ultrasound Simulations. 361-363 - Youngwoo Jang, Jiseob Byun, Soonbeom Kwon, Illyoung Choi, Dukyun Nam, Byungchul Tak, Gap-Joo Na, Young-Kyoon Suh:
K-RAF: A Kubernetes-based Resource Augmentation Framework for Edge Devices. 364-366 - Travis Higgins, Devki Nandan Jha, Rajiv Ranjan:
Swarm Storm: An Automated Chaos Tool for Docker Swarm Applications. 367-369 - Jirí Jaros, Radek Duchon:
Acceleration of Ultrasound Neurostimulation Using Mixed-Precision Arithmetic. 370-372 - Sungsoo Kim, Choon Seo Park, Taewhi Lee, Kihyuk Nam:
Constrained Approximate Query Processing with Error and Response Time-Bound Guarantees for Efficient Big Data Analytics. 373-376 - Achilleas Tzenetopoulos, George Lentaris, Aimilios Leftheriotis, Panos Chrysomeris, Javier Palomares, Estefanía Coronado, Raman Kazhamiakin, Dimitrios Soudris:
Seamless HW-accelerated AI serving in heterogeneous MEC Systems with AI@EDGE. 377-380 - Valerio De Caro, Christos Chronis, Massimo Coppola, Vincenzo Lomonaco, Claudio Gallicchio, Konstantinos Tserpes, Davide Bacciu:
TEACHING Platform for Human-Centric Autonomous Applications: Design and Overview. 381-384 - Aristotelis Kretsis, Panagiotis C. Kokkinos, Emmanouel A. Varvarigos, Dimitris Syrivelis, Paraskevas Bakopoulos, Márton Sipos, Marcell Fehér, Daniel Enrique Lucani, José Manuel Bernabé Murcia, Antonio F. Skarmeta, Ivan Paez, Luca Cominardi, Michael Mercier, Pedro Velho, Yiannis Georgiou, Charalampos Mainas, Anastassios Nanos, Javier Martin, Aitor Fernández Gómez, Roberto Gonzalez, Panos Ilias, Theodoros Chalazas, Keshav Chintamani:
EMPYREAN: Trustworthy, Cognitive and AI-driven Collaborative Associations of IoT Devices and Edge Resources for Data Processing. 385-388 - Nikolaos Tampouratzis, Ioannis Papaefstathiou:
Fast, Accurate and Distributed Simulation of novel HPC systems incorporating ARM and RISC-V CPUs. 389-392 - Claudio Cicconetti, Emanuele Carlini, Raphael Hetzel, Richard Mortier, Antonio Paradell, Markus Sauer:
EDGELESS: A Software Architecture for Stateful FaaS at the Edge. 393-396 - Jacopo Massa:
Towards a Comprehensive Approach to Resource and Conflict Management in Cloud-Edge Settings. 397-400 - Edoardo Tinto, Tullio Vardanega:
A runtime infrastructure for the Continuum of Computing. 401-404 - Mbasa Joaquim Molo:
Trade-off Analysis between Knowledge Distillation and Federated Learning in Distributed Edge System. 405-408 - Adeel Aslam, Giovanni Simonini:
Efficient Stream Join Processing: Novel Approaches and Challenges. 409-412 - Shaohan Huang, Zhongzhi Luan:
Semantic-Aware Log Understanding and Analysis. 413-416 - Federica Montesano:
Full-Stack Revision of Memory and Data Management in PDES on Multi-Core Machines. 417-420
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