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