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CORDIS - Risultati della ricerca dell’UE
CORDIS

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

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Efficiency database and design guide (si apre in una nuova finestra)

Public release of database of execution efficiency in terms of performance, power, and energy usage.

Complete performance and energy models (si apre in una nuova finestra)

Publication and release of performance and energy models.

Profiling and instrumentation tools (si apre in una nuova finestra)

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

Core set of sparse computation features (si apre in una nuova finestra)

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 (si apre in una nuova finestra)

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

Reordering Library (si apre in una nuova finestra)

Publication and source release of the reordering library by Simula.

SuperTwin and API (si apre in una nuova finestra)

Publication on the SuperTwin tool that describes its API and use-cases

Mixed precision support in SparCity Framework (si apre in una nuova finestra)

Publication and source release of mixed precision support of SparCity framework

Visualization tools (si apre in una nuova finestra)

Release of first version of the visualization tools for the current performance, power and energy usage, and communication and data movement patterns.

Topology-aware heterogeneous multi-level partitioner (si apre in una nuova finestra)

Source code release and a publication on topology-aware heterogeneous multi-level partitioner

Fully functioning code generator (si apre in una nuova finestra)

SU will release the code generator source code to public along with its documentation.

Microbenchmarking tools (si apre in una nuova finestra)

Publications and release of microbenchmarking tools

Mid-term usability report of the SparCity framework (si apre in una nuova finestra)

Simula will collect the results of testing the SparCity Framework on the sample use-cases and share the scientific findings with the public.

Scientific evaluation report of the SparCity framework (si apre in una nuova finestra)

Simula will release an evaluation report on the SparCity framework based on the partners' scientific findings and the use-cases of SparCity.

2nd Workshop about the SparCity framework and the modeling tools (si apre in una nuova finestra)

LMU will organize the second workshop that demonstrates the SparCity tools and provides tutorials on how to use them.

Prototype of performance and energy models (si apre in una nuova finestra)

Demonstration of performance and energy models

Prototype for the dynamic topology information system (si apre in una nuova finestra)

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.

Prototype of kernel template generator and kernel analyzer (si apre in una nuova finestra)

We will release the prototype of a source-to-source compiler that generates a kernel template auto-tuned for the target device.

1st Workshop about the SparCity framework and the modeling tools (si apre in una nuova finestra)

LMU will organize a workshop to demonstrate the Sparcity framework and its tools.

Pubblicazioni

Modelling Data Locality of Sparse Matrix-Vector Multiplication on the A64FX. (si apre in una nuova finestra)

Autori: Sergej Breiter, James D. Trotter, and Karl Fürlinger
Pubblicato in: Association for Computing Machinery, 2023
Editore: ACM
DOI: 10.1145/3624062.3624198

Bringing Order to Sparsity: A Sparse Matrix Reordering Study on Multicore CPUs. (si apre in una nuova finestra)

Autori: James D. Trotter, Sinan Ekmekçibaşı, Johannes Langguth, Tugba Torun, Emre Düzakın, Aleksandar Ilic, and Didem Unat
Pubblicato in: SC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2023
Editore: ACM
DOI: 10.1145/3581784.3607046

iPUG for Multiple Graphcore IPUs: Optimizing Performance and Scalability of Parallel Breadth-First Search (si apre in una nuova finestra)

Autori: Luk Burchard, Xing Cai, Johannes Langguth
Pubblicato in: 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC), 2021, Pagina/e 162-171
Editore: 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. (si apre in una nuova finestra)

Autori: Alexandre Rodrigues, Leonel Sousa and Alexandar Ilic
Pubblicato in: High Performance Computing. ISC High Performance 2023. Lecture Notes in Computer Science, 2023
Editore: Springer, Cham.
DOI: 10.1007/978-3-031-40843-4_36

Precise event sampling-based data locality tools for AMD multicore architectures (si apre in una nuova finestra)

Autori: Muhammad Aditya Sasongko, Milind Chabbi, Paul H. J. Kelly, Didem Unat
Pubblicato in: Concurrency Computat Pract Exper., 2023, ISSN 1532-0626
Editore: John Wiley and Sons Ltd.
DOI: 10.1002/cpe.7707

Mixed and Multi-Precision SpMV for GPUs with Row-wise Precision Selection (si apre in una nuova finestra)

Autori: Erhan Tezcan, Tugba Torun, Fahrican Koşar, Kamer Kaya, and Didem Unat
Pubblicato in: IEEE 34th International Symposium on Computer Architecture and High Performance Computing, 2022
Editore: IEEE
DOI: 10.1109/sbac-pad55451.2022.00014

Explaining the Performance of Supervised and Semi-Supervised Methods for Automated Sparse Matrix Format Selection (si apre in una nuova finestra)

Autori: Sunidhi Dhandhania, Akshay Deodhar, Konstantin Pogorelov, Swarnendu Biswas, Johannes Langguth
Pubblicato in: ICPP Workshops '21: 50th International Conference on Parallel Processing Workshop, 2021
Editore: ACM
DOI: 10.1145/3458744.3474049

Using GNNs for Misinformation Spreader Detection via Assortativity-Aware Node Label Classification in Twitter Networks (si apre in una nuova finestra)

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

Degree-Aware Kernels for Computing Jaccard Weights on GPUs (si apre in una nuova finestra)

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

Tensor-Accelerated Fourth-Order Epistasis Detection on GPUs (si apre in una nuova finestra)

Autori: Ricardo Nobre, Aleksandar Ilic, Sergio Santander-Jiménez, and Leonel Sousa
Pubblicato in: 51st International Conference on Parallel Processing (ICPP ’22), 2022
Editore: ACM
DOI: 10.1145/3545008.3545066

Unlocking Personalized Healthcare on Modern CPUs/GPUs: Three-way Gene Interaction Study. (si apre in una nuova finestra)

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

A Profiling-based Approach to Cache Partitioning of Program Data (si apre in una nuova finestra)

Autori: Sergej Breiter, Josef Weidendorfer, Minh Thanh Chung and Karl Fürlinger
Pubblicato in: Proceedings of the 23rd International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT’22), 2022
Editore: Springer Lecture Notes in Computer Science (LNCS)
DOI: 10.1007/978-3-031-29927-8_35

Fast and High-Quality Influence Maximization on Multiple GPUs (si apre in una nuova finestra)

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

Interpreting High Order Epistasis Using Sparse Transformers. (si apre in una nuova finestra)

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

Fourth-Order Exhaustive Epistasis Detection for the xPU Era (si apre in una nuova finestra)

Autori: Ricardo Nobre, Aleksandar Ilic, Sergio Santander-Jiménez, Leonel Sousa
Pubblicato in: 50th International Conference on Parallel Processing, 2021, Pagina/e 1-10, ISBN 9781450390682
Editore: ACM
DOI: 10.1145/3472456.3472509

Boosting Graph Embedding on a Single GPU (si apre in una nuova finestra)

Autori: Amro Alabsi Aljundi, Taha Atahan Akyildiz, Kamer Kaya
Pubblicato in: IEEE Transactions on Parallel and Distributed Systems, Numero 10459219, 2022, Pagina/e 3092 - 3105, ISSN 1045-9219
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpds.2021.3129617

Fast and error-adaptive influence maximization based on Count-Distinct sketches (si apre in una nuova finestra)

Autori: Gökhan Göktürk, Kamer Kaya
Pubblicato in: Information Sciences, Numero Volume 655, January 2024, 119875, 2024, ISSN 1872-6291
Editore: Elsevier
DOI: 10.1016/j.ins.2023.119875

Mansard Roofline Model: Reinforcing the Accuracy of the Roofs (si apre in una nuova finestra)

Autori: Diogo Marques, Aleksandar Ilic, Leonel Sousa
Pubblicato in: ACM Transactions on Modeling and Performance Evaluation of Computing Systems, Numero 6/2, 2021, Pagina/e 1-23, ISSN 2376-3639
Editore: Association for Computing Machinery
DOI: 10.1145/3475866

PhyloMissForest: a random forest framework to construct phylogenetic trees with missing data (si apre in una nuova finestra)

Autori: Diogo Pinheiro; Sergio Santander-Jimenéz; Aleksandar Ilic
Pubblicato in: BMC Genomics, Numero vol. 2, no. 1, 2022, Pagina/e 1-21, ISSN 1471-2164
Editore: 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. (si apre in una nuova finestra)

Autori: James D. Trotter, Johannes Langguth and Xing Cai
Pubblicato in: Parallel Computing, 2023, ISSN 0167-8191
Editore: Elsevier BV
DOI: 10.1016/j.parco.2023.103051

Detailed Modeling of Heterogeneous and Contention-Constrained Point-to-Point MPI Communication (si apre in una nuova finestra)

Autori: Andreas Thune; Sven-Arne Reinemo; Tor Skeie; Xing Cai
Pubblicato in: IEEE Transactions on Parallel and Distributed Systems, 2023, ISSN 1045-9219
Editore: 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. (si apre in una nuova finestra)

Autori: Luk Burchard, Kristian Gregorius Hustad, Johannes Langguth and Xing Cai
Pubblicato in: Front. Phys. Sec. Statistical and Computational Physics, 2023, ISSN 2296-424X
Editore: Frontiers Media
DOI: 10.3389/fphy.2023.979699

iPUG: Accelerating Breadth-First Graph Traversals Using Manycore Graphcore IPUs (si apre in una nuova finestra)

Autori: Luk Burchard, Johannes Moe, Daniel Thilo Schroeder, Konstantin Pogorelov, Johannes Langguth
Pubblicato in: High Performance Computing - 36th International Conference, ISC High Performance 2021, Virtual Event, June 24 – July 2, 2021, Proceedings, Numero 12728, 2021, Pagina/e 291-309, ISBN 978-3-030-78712-7
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-78713-4_16

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