This thesis talks about techniques which can be used to optimize run time of algorithms. For a demonstration of these techniques algorithms from different fields were chosen, namely particle swarm optimization, circle drawing algorithm and image (matrix) rotation algorithm. These algorithms were written in Python 3, C language and assembly language using SIMD instructions. While writing these codes emphases was placed on code efficiency. These practices were in this thesis described and compared, same as the impact on algorithm optimization. Performed tests upheld expected potential of SIMD technology for optimization, but also that this approach cannot be used in all cases. In case of circle drawing the SIMD approach achieved more than ten...
The polyhedral model for loop parallelization has proved to be an effective tool for ad-vanced optim...
The purpose of optimization is to maximize the quality of lives, productivity in time, as well as in...
Many media processing algorithms suffer from long execution times, which are most often not acceptab...
The SpMV operation -- the multiplication of a sparse matrix with a dense vector -- is used in many s...
Traditional computer software is written for serial computation. To solve an optimization problem, a...
The nominal peak speeds of both serial and parallel computers is raising rapidly. At the same time h...
This thesis discusses how to optimize computational physics software for speed through maximizing th...
Bachelor's thesis is concerned with methods for global optimization. It deals with concept of optimi...
The multiplication of a sparse matrix with a dense vector is a performance critical computational ke...
The Cerebras CS-1 is a computing system based on a wafer-scale processor having nearly 400,000 compu...
The Single Instruction Multiple Data (SIMD) paradigm promises speedup at relatively low silicon area...
Programmers spent most of their time in speeding up a program. Sometimes, speeding up a program lead...
As an effective way of utilizing data parallelism in applications, SIMD architecture has been adopte...
This paper describes methods to adapt existing optimizing compilers for sequential languages to prod...
The paper is devoted to the methods of automatic parallelization and software optimization. The auth...
The polyhedral model for loop parallelization has proved to be an effective tool for ad-vanced optim...
The purpose of optimization is to maximize the quality of lives, productivity in time, as well as in...
Many media processing algorithms suffer from long execution times, which are most often not acceptab...
The SpMV operation -- the multiplication of a sparse matrix with a dense vector -- is used in many s...
Traditional computer software is written for serial computation. To solve an optimization problem, a...
The nominal peak speeds of both serial and parallel computers is raising rapidly. At the same time h...
This thesis discusses how to optimize computational physics software for speed through maximizing th...
Bachelor's thesis is concerned with methods for global optimization. It deals with concept of optimi...
The multiplication of a sparse matrix with a dense vector is a performance critical computational ke...
The Cerebras CS-1 is a computing system based on a wafer-scale processor having nearly 400,000 compu...
The Single Instruction Multiple Data (SIMD) paradigm promises speedup at relatively low silicon area...
Programmers spent most of their time in speeding up a program. Sometimes, speeding up a program lead...
As an effective way of utilizing data parallelism in applications, SIMD architecture has been adopte...
This paper describes methods to adapt existing optimizing compilers for sequential languages to prod...
The paper is devoted to the methods of automatic parallelization and software optimization. The auth...
The polyhedral model for loop parallelization has proved to be an effective tool for ad-vanced optim...
The purpose of optimization is to maximize the quality of lives, productivity in time, as well as in...
Many media processing algorithms suffer from long execution times, which are most often not acceptab...