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Ivan Simecek

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2020 – today

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2024
[j12]
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  - journals/paapp/KasparS24
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Jirí Kaspar, Ivan Simecek:
Parallel CRC optimisations on the x64 architecture: a per-partes method. Int. J. Parallel Emergent Distributed Syst. 39(3): 292-316 (2024)
2023
[j11]
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Ivan Simecek, Claudio Kozický:
A parallel algorithm for approximating the silhouette using a ball tree. J. Parallel Distributed Comput. 173: 115-125 (2023)
[j10]
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Adam Simek, Ivan Simecek:
Design of a modern fast Fourier transform and cache effective bit-reversal algorithm. Int. J. Parallel Emergent Distributed Syst. 38(3): 229-248 (2023)
2021
[j9]
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  - journals/concurrency/KozickyS21
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Claudio Kozický, Ivan Simecek:
Joint direct and transposed sparse matrix-vector multiplication for multithreaded CPUs. Concurr. Comput. Pract. Exp. 33(13) (2021)
2020
[c27]
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Ivan Simecek, Claudio Kozický, Daniel Langr, Pavel Tvrdík:
Space-Efficient k-d Tree-Based Storage Format for Sparse Tensors. HPDC 2020: 29-33

2010 – 2019

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2018
[j8]
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Viktor Chlumský, Jaroslav Sloup, Ivan Simecek:
Improved Corners with Multi-Channel Signed Distance Fields. Comput. Graph. Forum 37(1): 273-287 (2018)
[j7]
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Daniel Langr, Ivan Simecek:
Analysis of Memory Footprints of Sparse Matrices Partitioned Into Uniformly-Sized Blocks. Scalable Comput. Pract. Exp. 19(3): 275-292 (2018)
2017
[c26]
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Daniel Langr, Ivan Simecek:
On Memory Footprints of Partitioned Sparse Matrices. FedCSIS 2017: 513-521
[c25]
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Ivan Simecek, Daniel Langr, Ivan Kotenkov:
Multilayer Approach for Joint Direct and Transposed Sparse Matrix Vector Multiplication for Multithreaded CPUs. PPAM (1) 2017: 47-56
[c24]
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  - conf/synasc/MituraSK17
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Peter Mitura, Ivan Simecek, Ivan Kotenkov:
Effective Construction of Convex Hull Algorithms. SYNASC 2017: 105-112
2016
[j6]
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Ivan Simecek, Richard Fritsch, Daniel Langr, Róbert Lórencz:
Parallel Solver of Large Systems of Linear Inequalities Using Fourier-Motzkin Elimination. Comput. Informatics 35(6): 1307-1337 (2016)
[j5]
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Daniel Langr, Pavel Tvrdík, Ivan Simecek:
AQsort: Scalable Multi-Array In-Place Sorting with OpenMP. Scalable Comput. Pract. Exp. 17(4): 369-391 (2016)
[c23]
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Daniel Langr, Ivan Simecek, Tomás Dytrych:
Block Iterators for Sparse Matrices. FedCSIS 2016: 695-704
[c22]
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Ivan Simecek, Daniel Langr:
Efficient parallel evaluation of block properties of sparse matrices. FedCSIS 2016: 709-716
2015
[j4]
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  - journals/ijpp/LangrTSD15
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Daniel Langr, Pavel Tvrdík, Ivan Simecek, Tomás Dytrych:
Downsampling Algorithms for Large Sparse Matrices. Int. J. Parallel Program. 43(5): 679-702 (2015)
[c21]
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Ivan Simecek, Daniel Langr:
Space and Execution Efficient Formats for Modern Processor Architectures. SYNASC 2015: 98-105
[c20]
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  - conf/synasc/KhuniL15
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Jiri Khun, Ivan Simecek, Róbert Lórencz:
GPU Solver for Systems of Linear Equations with Infinite Precision. SYNASC 2015: 121-124
2014
[j3]
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  - journals/comsis/SimecekT14
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Ivan Simecek, Pavel Tvrdík:
A new code transformation technique for nested loops. Comput. Sci. Inf. Syst. 11(4): 1381-1416 (2014)
[j2]
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Daniel Langr, Ivan Simecek, Pavel Tvrdík, Tomás Dytrych:
Large-Scale Visualization of Sparse Matrices. Scalable Comput. Pract. Exp. 15(1) (2014)
[j1]
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Ivan Simecek, Daniel Langr:
Tree-based Space Efficient Formats for Storing the Structure of Sparse Matrices. Scalable Comput. Pract. Exp. 15(1) (2014)
[c19]
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Ivan Simecek, Daniel Langr, Jan Trdlicka:
Efficient Converting of Large Sparse Matrices to Quadtree Format. SYNASC 2014: 122-129
[i1]
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Daniel Langr, Ivan Simecek, Pavel Tvrdík:
Loading Large Sparse Matrices Stored in Files in the Adaptive-Blocking Hierarchical Storage Format. CoRR abs/1412.8299 (2014)
2013
[c18]
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Daniel Langr, Ivan Simecek, Pavel Tvrdík:
Storing Sparse Matrices to Files in the Adaptive-Blocking Hierarchical Storage Format. FedCSIS 2013: 479-486
[c17]
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Ivan Simecek, Pavel Tvrdík:
Dynamic loop reversal - the new code transformation technique. FedCSIS 2013: 1575-1582
[c16]
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Daniel Langr, Ivan Simecek, Pavel Tvrdík, Tomás Dytrych:
Scalable Parallel Generation of Very Large Sparse Benchmark Matrices. PPAM (1) 2013: 178-187
[c15]
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Ivan Simecek, Daniel Langr, Erik Srnec:
The Study of Impact of Matrix-Processor Mapping on the Parallel Sparse Matrix-Vector Multiplication. SYNASC 2013: 321-328
[c14]
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Daniel Langr, Ivan Simecek, Pavel Tvrdík, Tomás Dytrych:
Parallel Data Acquisition for Visualization of Very Large Sparse Matrices. SYNASC 2013: 336-343
[c13]
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Ivan Simecek, Daniel Langr, Pavel Tvrdík:
Space Efficient Formats for Structure of Sparse Matrices Based on Tree Structures. SYNASC 2013: 344-351
2012
[c12]
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  - conf/cse/imecek12
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Ivan Simecek:
A New Approach for Indexing Powder Diffraction Data Based on Dichotomy Method. CSE 2012: 124-129
[c11]
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Daniel Langr, Ivan Simecek, Pavel Tvrdík, Tomás Dytrych, Jerry P. Draayer:
Adaptive-Blocking Hierarchical Storage Format for Sparse Matrices. FedCSIS 2012: 545-551
[c10]
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Ivan Simecek, Daniel Langr, Pavel Tvrdík:
Space-efficient Sparse Matrix Storage Formats for Massively Parallel Systems. HPCC-ICESS 2012: 54-60
[c9]
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  - conf/softcomp/Simecek12
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Ivan Simecek:
A New Approach for Indexing Powder Diffraction Data Suitable for GPGPU Execution. SOCO 2012: 409-416
[c8]
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Ivan Simecek, Daniel Langr, Pavel Tvrdík:
Minimal Quadtree Format for Compression of Sparse Matrices Storage. SYNASC 2012: 359-364

2000 – 2009

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2009
[c7]
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Ivan Simecek:
Sparse Matrix Computations Using the Quadtree Storage Format. SYNASC 2009: 168-173
2007
[c6]
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Ivan Simecek, Pavel Tvrdík:
Sparse Matrix-Vector Multiplication - Final Solution?. PPAM 2007: 156-165
2006
[c5]
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  - conf/synasc/TvrdikS06
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Pavel Tvrdík, Ivan Simecek:
A New Approach for Accelerating the Sparse Matrix-Vector Multiplication. SYNASC 2006: 156-163
2005
[c4]
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Pavel Tvrdík, Ivan Simecek:
A New Diagonal Blocking Format and Model of Cache Behavior for Sparse Matrices. PPAM 2005: 164-171
2004
[c3]
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  - conf/icppw/SimecekT04
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Ivan Simecek, Pavel Tvrdík:
Analytical Model for Analysis of Cache Behavior during Cholesky Factorization and Its Variants. ICPP Workshops 2004: 190-197
[c2]
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  - conf/naa/TvrdikS04
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Pavel Tvrdík, Ivan Simecek:
Performance Optimization and Evaluation for Linear Codes. NAA 2004: 566-573
2003
[c1]
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Pavel Tvrdík, Ivan Simecek:
Analytical Modeling of Optimized Sparse Linear Code. PPAM 2003: 207-216

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