SparCity: An Optimization and Co-design Framework for Sparse Computation

Project Information

SPARCITY

Grant agreement ID: 956213

DOI 10.3030/956213

Project closed

EC signature date 2 December 2020

Start date 1 April 2021

End date 31 March 2024

Funded under

• INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)

Total cost € 2 605 472,49

EU contribution € 1 302 736,25

Coordinated by

KOC UNIVERSITY
Türkiye

Deliverables

Demonstrators, pilots, prototypes (2)

Prototype of performance and energy models

Demonstration of performance and energy models

Prototype for the dynamic topology information system

This deliverable will release a prototype of a dynamic topology information system that integrates existing data sources such as the hwloc and vendor-specific tools to capture the complex setup of modern HPC systems.

Other (3)

Profiling and instrumentation tools

Profiling and instrumentation tools will be developed by INESC ID and shared with other partners and public.

Core set of sparse computation features

KU will develop core set of sparse matrix features for ML learning techniques and make it available to the general public as a publication or report.

ML-based prediction model

Machine learning based prediction model and its source code for sparse computation will be made public.

Open Research Data Pilot (1)

Microbenchmarking tools

Publications and release of microbenchmarking tools

Publications

Conference proceedings (15)

Modelling Data Locality of Sparse Matrix-Vector Multiplication on the A64FX.

Author(s): Sergej Breiter, James D. Trotter, and Karl Fürlinger
Published in: Association for Computing Machinery, 2023
Publisher: ACM
DOI: 10.1145/3624062.3624198

Bringing Order to Sparsity: A Sparse Matrix Reordering Study on Multicore CPUs.

Author(s): James D. Trotter, Sinan Ekmekçibaşı, Johannes Langguth, Tugba Torun, Emre Düzakın, Aleksandar Ilic, and Didem Unat
Published in: 2023
Publisher: ACM
DOI: 10.1145/3581784.3607046

iPUG for Multiple Graphcore IPUs: Optimizing Performance and Scalability of Parallel Breadth-First Search

Author(s): Luk Burchard, Xing Cai, Johannes Langguth
Published in: 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC), 2021, Page(s) 162-171
Publisher: IEEE
DOI: 10.1109/hipc53243.2021.00030

Performance Modelling-driven Optimization of RISC-V Hardware for Efficient SpMV. Proceedings of the International workshop on RISC-V for HPC.

Author(s): Alexandre Rodrigues, Leonel Sousa and Alexandar Ilic
Published in: High Performance Computing. ISC High Performance 2023. Lecture Notes in Computer Science, 2023
Publisher: Springer, Cham.
DOI: 10.1007/978-3-031-40843-4_36

Precise event sampling-based data locality tools for AMD multicore architectures

Author(s): Muhammad Aditya Sasongko, Milind Chabbi, Paul H. J. Kelly, Didem Unat
Published in: Concurrency Computat Pract Exper., 2023, ISSN 1532-0626
Publisher: John Wiley and Sons Ltd.
DOI: 10.1002/cpe.7707

Mixed and Multi-Precision SpMV for GPUs with Row-wise Precision Selection

Author(s): Erhan Tezcan, Tugba Torun, Fahrican Koşar, Kamer Kaya, and Didem Unat
Published in: IEEE 34th International Symposium on Computer Architecture and High Performance Computing, 2022
Publisher: IEEE

Explaining the Performance of Supervised and Semi-Supervised Methods for Automated Sparse Matrix Format Selection

Author(s): Sunidhi Dhandhania, Akshay Deodhar, Konstantin Pogorelov, Swarnendu Biswas, Johannes Langguth
Published in: ICPP Workshops '21: 50th International Conference on Parallel Processing Workshop, 2021
Publisher: ACM
DOI: 10.1145/3458744.3474049

Using GNNs for Misinformation Spreader Detection via Assortativity-Aware Node Label Classification in Twitter Networks

Author(s): Asep Maulana, Johannes Langguth
Published in: 2023 Tenth International Conference on Social Networks Analysis, Management and Security (SNAMS), 2023
Publisher: IEEE
DOI: 10.1109/snams60348.2023.10375407

Degree-Aware Kernels for Computing Jaccard Weights on GPUs

Author(s): Amro Alabsi Aljundi, Taha Atahan Akyildiz, Kamer Kaya
Published in: 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2022, ISBN 978-1-6654-8106-9
Publisher: IEEE
DOI: 10.1109/ipdps53621.2022.00092

Tensor-Accelerated Fourth-Order Epistasis Detection on GPUs

Author(s): Ricardo Nobre, Aleksandar Ilic, Sergio Santander-Jiménez, and Leonel Sousa
Published in: 51st International Conference on Parallel Processing (ICPP ’22), 2022
Publisher: ACM

Unlocking Personalized Healthcare on Modern CPUs/GPUs: Three-way Gene Interaction Study.

Author(s): Diogo Marques, Rafael Campos, Sergio Santander-Jiménez, Zakhar Matveev, Leonel Sousa, and Aleksandar Ilic
Published in: IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2022
Publisher: IEEE
DOI: 10.1109/ipdps53621.2022.00023

A Profiling-based Approach to Cache Partitioning of Program Data

Author(s): Sergej Breiter, Josef Weidendorfer, Minh Thanh Chung and Karl Fürlinger
Published in: Proceedings of the 23rd International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT’22), 2022
Publisher: Springer Lecture Notes in Computer Science (LNCS)

Fast and High-Quality Influence Maximization on Multiple GPUs

Author(s): Gökhan Göktürk, Kamer Kaya
Published in: 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2022, ISBN 978-1-6654-8106-9
Publisher: IEEE
DOI: 10.1109/ipdps53621.2022.00093

Interpreting High Order Epistasis Using Sparse Transformers.

Author(s): Miguel Graça, Diogo Marques, Sergio Santander-Jiménez, Leonel Sousa, and Aleksandar Ilic
Published in: IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), 2023
Publisher: IEEE
DOI: 10.1145/3580252.3586982

Fourth-Order Exhaustive Epistasis Detection for the xPU Era

Author(s): Ricardo Nobre, Aleksandar Ilic, Sergio Santander-Jiménez, Leonel Sousa
Published in: 50th International Conference on Parallel Processing, 2021, Page(s) 1-10, ISBN 9781450390682
Publisher: ACM
DOI: 10.1145/3472456.3472509

Peer reviewed articles (7)

Boosting Graph Embedding on a Single GPU

Author(s): Amro Alabsi Aljundi, Taha Atahan Akyildiz, Kamer Kaya
Published in: IEEE Transactions on Parallel and Distributed Systems, Issue 10459219, 2022, Page(s) 3092 - 3105, ISSN 1045-9219
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpds.2021.3129617

Fast and error-adaptive influence maximization based on Count-Distinct sketches

Author(s): Gökhan Göktürk, Kamer Kaya
Published in: Information Sciences, Issue Volume 655, January 2024, 119875, 2024, ISSN 1872-6291
Publisher: Elsevier
DOI: 10.1016/j.ins.2023.119875

Mansard Roofline Model: Reinforcing the Accuracy of the Roofs

Author(s): Diogo Marques, Aleksandar Ilic, Leonel Sousa
Published in: ACM Transactions on Modeling and Performance Evaluation of Computing Systems, Issue 6/2, 2021, Page(s) 1-23, ISSN 2376-3639
Publisher: Association for Computing Machinery
DOI: 10.1145/3475866

PhyloMissForest: a random forest framework to construct phylogenetic trees with missing data

Author(s): Diogo Pinheiro; Sergio Santander-Jimenéz; Aleksandar Ilic
Published in: BMC Genomics, Issue 14712164, 2022, Page(s) 1-21, ISSN 1471-2164
Publisher: BioMed Central
DOI: 10.1186/s12864-022-08540-6

Targeting performance and user-friendliness: GPU-accelerated finite element computation with automated code generation in FEniCS.

Author(s): James D. Trotter, Johannes Langguth and Xing Cai
Published in: Parallel Computing, 2023, ISSN 0167-8191
Publisher: Elsevier BV
DOI: 10.1016/j.parco.2023.103051

Detailed Modeling of Heterogeneous and Contention-Constrained Point-to-Point MPI Communication

Author(s): Andreas Thune; Sven-Arne Reinemo; Tor Skeie; Xing Cai
Published in: IEEE Transactions on Parallel and Distributed Systems, 2023, ISSN 1045-9219
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpds.2023.3253881

Enabling Unstructured-Mesh Computation on Massively Tiled AI-Processors: An Example of Accelerating In-Silico Cardiac Simulation.

Author(s): Luk Burchard, Kristian Gregorius Hustad, Johannes Langguth and Xing Cai
Published in: Front. Phys. Sec. Statistical and Computational Physics, 2023, ISSN 2296-424X
Publisher: Frontiers Media
DOI: 10.3389/fphy.2023.979699

Book chapters (1)

iPUG: Accelerating Breadth-First Graph Traversals Using Manycore Graphcore IPUs

Author(s): Luk Burchard, Johannes Moe, Daniel Thilo Schroeder, Konstantin Pogorelov, Johannes Langguth
Published in: High Performance Computing - 36th International Conference, ISC High Performance 2021, Virtual Event, June 24 – July 2, 2021, Proceedings, Issue 12728, 2021, Page(s) 291-309, ISBN 978-3-030-78712-7
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-78713-4_16