Algorithms for Parallel and Distributed Computing Systems
Program
Studentská grantová soutěž ČVUT
Departments
Investigators
Code
SGS14/106/OHK3/1T/18
Period
2014
Description
The proposed project is based on previous research results in the field of parallel and distributed computing systems. It is aimed at massively parallel computing, GPU computing, cluster computing, and global grid computing systems. More specifically, the project is going to focus 1) on the reseach of the architecture of the nondedicated cluster architecture with the focus on the algorithms for distributed task scheduling in such clusters, 2) on the design of efficient algorithms for crystal structure determination based on powder diffraction method on massively parallel GPU clusters, 3) on the parallelization of immune-system-inspired algorithms on GPU clusters, 4) on the design of efficient algorithms for data acquisition and visualization of very large sparse matrices mapped row-wise/column-wise on processors of massively parallel multiprocessor systems, and 5) on the reseach of heuristic algorithms for resource allocation in worldwide computing grids.
Application of paralelization of scientific computations
Program
Studentská grantová soutěž ČVUT
Departments
Investigators
Code
SGS12/097/OHK3/1T/18
Period
2012
Description
This project consists of several research subprojects that investigate various interesting parallel programming aspects.
The first research project concerns with sparse matrix storage formats. It is focused on aspects of quad-tree abstract data type for sparse matrix representation. Preliminary results indicate high potential of quad-tree format, but it is necessary to implement more functions and measure the performance thoroughly.
The next part of the project is algorithms for visualization of very large sparse matrices. The recently developed algorithm is independent of partitioning of a matrix among individual processors of a parallel computer. The price for this independence is that the memory requirements are proportional to the size of the image, which limits the detail investigation of the matrix structure. The goal is to develop memory efficient algorithms for visualization of particular types of sparse matrices that will lead to the possibility of creation of much bigger re
Cryptology and security
Program
Studentská grantová soutěž ČVUT
Departments
Investigators
Code
SGS15/120/OHK3/1T/18
Period
2015
Description
The Applicated Numerics and Cryptology research group studies various security components of information systems, especially at the research and development true random generators and physically unclonable functions, cryptoanalysis of block and stream ciphers, factorization of large numbers and efficient solving large systems of linear equations. The proposed project also addresses these thematic research areas.
Cryptology, security, and parallel computations
Program
Studentská grantová soutěž ČVUT
Investigators
Code
SGS16/122/OHK3/1T/18
Period
2016
Description
This project is aimed at several aspects of security of information systems inclusing identification of potential security threats. Main topics are following: cryptoanalysis of block and stream ciphers, efficient
solving large systems of linear equations with an infinite precision, and the research and development true random generators and physically
unclonable functions,
Design of efficient parallel algorithms for solution of important engineer's problems
Program
Studentská grantová soutěž ČVUT
Investigators
Code
SGS20/212/OHK3/3T/18
Period
2020 - 2022
Description
The proposed project is based on previous research results in the field of parallel and distributed algorithms for solution of some important engineer's problems. More specifically, the project is going to focus 1) on the methodology and algorithms for a systematic evaluation of sparse matrix and tensor storage formats that would allow a complex understanding of their properties, 2) on the application of machine learning in network security, 3) on the most advanced computer science methods in astronomy to allow preprocessing, storing, sharing, and analyzing of petabytes of data flowing continuously from astronomical instruments, 4) on the research of algorithms for multithreaded memoization system focused on their effective implementation and parallelization.
Design of efficient parallel algorithms for solution of important engineer's problems
Program
Studentská grantová soutěž ČVUT
Investigators
Code
SGS17/215/OHK3/3T/18
Period
2017 - 2019
Description
The proposed project is based on previous research results in the field of parallel and distributed algorithms for solution of some important engineer's problems. More specifically, the project is going to focus 1) on the most advanced computer science methods in astronomy to allow preprocessing, storing, sharing, and analysing of petabytes of data flowing continuously from astronomical instruments, 2) on the methodology and algorithms for a systematic evaluation of sparse matrix storage formats that would allow a complex understanding of their properties, 3) on the research of algorithms for solving the convex hull problem in 2 and 3 dimensions, focused on their effective implementation and parallelization.
Design of efficient parallel algorithms for solution of important engineer's problems II
Program
Studentská grantová soutěž ČVUT
Departments
Investigators
Code
SGS23/209/OHK3/3T/18
Period
2023 - 2025
Description
The proposed project is based on previous research results in the field of parallel and distributed algorithms for solution of some important engineer's problems. More specifically, the project is going to focus 1) on the most advanced computer science methods in astronomy to allow preprocessing, storing, sharing, and analyzing of petabytes of data flowing continuously from astronomical instruments, 2) on the methodology and algorithms for a systematic evaluation of sparse matrix and tensor storage formats that would allow a complex understanding of their properties, 3) on parallel algorithms for reconstruction of physical objects from recorded data.
Experimental grid for numerical linear algebra
Program
CESNET - Fond rozvoje
Provider
Another domestic provider
Departments
Investigators
Code
CESNET č. 390/2010
Period
2010 - 2012
Description
The main goal of this project is to create an experimental computing grid for scientific computations mainly focused on linear algebra. This grid will execute the special version of libraries (BLAS/LAPACK) for the numeric linear algebra. When the user wants to execute some computations, the heuristic in the client part estimates if it will be faster to do a local computation or send input data to the grid and wait for reply (output data).
Parallel Input/Output Algorithms for Very Large Sparse Matrices
Program
Standard projects
Provider
Czech Science Foundation
Departments
Investigators
Code
GAP202/12/2011
Period
2012 - 2014
Description
Algorithms for solving so called "Grand challenge problems" lead to huge data sets, typically organized as sparse matrices. This project addresses the research of effective and scalable algorithms and data structures for input/output operations on very large sparse matrices that due to their size must be stored and processed on massively parallel computers with tens or hundreds of thousands of processors. Such matrices consist of trillions of nonzero entries. The project focuses on research of new binary file formats for storing such matrices, on research of data structures and scalable algorithms for effective loading such matrices into massively parallel solvers, and on research of memory-effective formats for representation of such matrices in computer memory. Finally, the project also aims at research of effective and scalable algorithms for visualization of very large sparse matrices on massively parallel computers. Together with theoretical parts, the project involves verification of proposed algorithms and data structures on real massively parallel computers.