2020
DOI: 10.1002/cpe.5854
|View full text |Cite
|
Sign up to set email alerts
|

Compilation of MATLAB computations to CPU/GPU via C/OpenCL generation

Abstract: In order to take advantage of the processing power of current computing platforms, programmers typically need to develop software versions for different target devices. This task is time-consuming and requires significant programming and computer architecture expertise. A possible and more convenient alternative is to start with a single high-level description of a program with minimum implementation details, and generate custom implementations according to the target platform. In this paper, we use MATLAB as … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(3 citation statements)
references
References 23 publications
0
3
0
Order By: Relevance
“…In contrast, some functionalities, such as loops operating on matrices in MATLAB, tends to be slow. 13 So, the computational cost becomes a crucial factor, making this software unfeasible for a number of real-time applications, that demands thousands of sequential calculations.…”
Section: Accelerating Matlab/simulink © Implementationsmentioning
confidence: 99%
See 1 more Smart Citation
“…In contrast, some functionalities, such as loops operating on matrices in MATLAB, tends to be slow. 13 So, the computational cost becomes a crucial factor, making this software unfeasible for a number of real-time applications, that demands thousands of sequential calculations.…”
Section: Accelerating Matlab/simulink © Implementationsmentioning
confidence: 99%
“…In practice, the software becomes especially useful in application development and in the proof‐of‐concept or validation of strategies and models, especially in robotics contexts 12 ). In contrast, some functionalities, such as loops operating on matrices in MATLAB, tends to be slow 13 . So, the computational cost becomes a crucial factor, making this software unfeasible for a number of real‐time applications, that demands thousands of sequential calculations.…”
Section: Introductionmentioning
confidence: 99%
“…Source-to-source compilers implemented using the LARA framework have a common abstraction layer for accessing the AST, and analyses are implemented using scripts written in JavaScript. The abstraction layer is language-agnostic, so there are LARA compilers for several languages (e.g., C/C++ [10], MATLAB [48]) using the same abstraction.…”
Section: Lara and Kadabramentioning
confidence: 99%