Publications

You can find my articles on my Google Scholar profile, too.

[9] Yıltan Hassan Temucin, Whit Schonbein, Scott Levy, Amirhossein Sojoodi, Ryan E Grant, Ahmad Afsahi, “Design and Implementation of MPI-Native GPU-Initiated MPI Partitioned Communication”, Proceedings of the workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W), pp. 1-12, DOI: 10.1109/SCW63240.2024.00065

[8] Hamed Sharifian, Amirhossein Sojoodi, Ahmad Afsahi, “A Topology- and Load-Aware Design for Neighborhood Allgather”, Proceedings of the IEEE International Conference on Cluster Computing (CLUSTER), pp. 1-12, DOI: 10.1109/CLUSTER59578.2024.00019

[7] Amirhossein Sojoodi, Yiltan Hassan Temucin, Ahmad Afsahi , “Enhancing Intra-Node GPU-to-GPU Performance in MPI + UCX through Multi-Path Communication”, Proceedings of the International Workshop on Extreme Heterogeneity Solutions (ExHET), pp. 1-6, DOI: 10.1145/3642961.3643800 - Best Paper Award.

[6] Pedram Alizadeh, Amirhossein Sojoodi, Yiltan Hassan Temucin, Ahmad Afsahi , “Efficient Process Arrival Pattern Aware Collective Communication for Deep Learning”, Proceedings of the European MPI Users’ Group Meeting (EuroMPI), pp. 68-78, DOI: 10.1145/3555819.3555857

[5] Philipp A. Witte, Russell J. Hewett, Kumar Saurabh, Amirhossein Sojoodi, Ranveer Chandra , “SciAI4Industry - Solving PDEs for industry-scale problems with deep learning”, arXiv (2022), pp. 1-11, DOI: 10.48550/arXiv.2211.12709

[4] Yiltan Hassan Temucin, Amirhossein Sojoodi, Pedram Alizadeh, Ahmad Afsahi , “Efficient Multi-Path NVLink / PCIe-Aware UCX based Collective Communication for Deep Learning”, Proceedings of the IEEE Symposium on High-Performance Interconnects (HOTI), pp. 1-10, DOI: 10.1109/HOTI52880.2021.00018

[3] Yiltan Hassan Temucin, Amirhossein Sojoodi, Pedram Alizadeh, Benjamin W Kitor, Ahmad Afsahi , “Accelerating Deep Learning using Interconnect-Aware UCX Communication for MPI Collectives”, IEEE Micro (2021), pp. 1-9, DOI: 10.1109/MM.2022.3148670

[2] Majid Salimi Beni, Amirhossein Sojoodi, Farshad Khunjush , “A GPU-Enabled Extension for Apache Ignite to Facilitate Running Genetic Algorithms”, Proceedings of the International Symposium on Computer Architecture and Digital Systems (CADS), pp. 1-8, DOI: 10.1109/CADS50570.2020.9211857

[1] Amirhossein Sojoodi, Majid Salimi Beni, Farshad Khunjush , “Ignite-GPU: a GPU-enabled in-memory computing architecture on clusters”, Journal of Supercomputing (2020), pp. 1-28, DOI: 10.1007/s11227-020-03390-z