ScholarLens Back to search
2011•Unpublished venueRequires access

Speedup simulation for OFDM over PLC channel using a multithreading GPU

Gerardo Laguna‐Sanchez, Alfonso Prieto‐Guerrero, Enrique Rodríguez-Colina

Open publisher page 2 citations

Abstract

The huge computing power available in some graphic cards may be used to significantly speedup scientific computing compared with common parallel clusters. The low price and virtually ubiquitous Graphics Processing Units (GPU), in conjunction with C style parallel programming tools, like CUDA (Compute Unified Device Architecture), allow the programmers to exploit their fine grain parallelism and multithreading management capacities to speedup generic purpose applications. In this paper, we expose our experience applying a multithreading GPU to speedup Monte Carlo simulations for an OFDM schema over a power-line communication (PLC) channel, making emphasis on practical considerations that help to reach the best performance for both, GPU and overall system.

About this research paper

What this paper is about

The huge computing power available in some graphic cards may be used to significantly speedup scientific computing compared with common parallel clusters. The low price and virtually ubiquitous Graphics Processing Units (GPU), in conjunction with C style parallel programming tools, like CUDA (Compute Unified Device Architecture), allow the programmers to exploit their fine grain parallelism and multithreading management capacities to speedup generic purpose applications. In this paper, we expose our experience applying a multithreading GPU to speedup Monte Carlo simulations for an OFDM schema over a power-line communication (PLC) channel, making emphasis on practical considerations that help to reach the best performance for both, GPU and overall system.

Why it matters

OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The huge computing power available in some graphic cards may be used to significantly speedup scientific computing compared with common parallel clusters. The low price and virtually ubiquitous Graphics Processing Units (GPU), in conjunction with C style parallel programming tools, like CUDA (Compute Unified Device Architecture), allow the programmers to exploit their fine grain parallelism and multithreading management capacities to speedup generic purpose applications. In this paper, we expose our experience applying a multithreading GPU to speedup Monte Carlo simulations for an OFDM schema over a power-line communication (PLC) channel, making emphasis on practical considerations that help to reach the best performance for both, GPU and overall system.

Key concepts: Speedup, Multithreading, Computer science, Parallel computing, CUDA, Graphics, Exploit, Pascal (unit)

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
Speedup simulation for OFDM over PLC channel using a multithreading GPU — Research Paper | ScholarLens