Processing large volumes of information generally requires massive amounts of computational power, which consumes a significant amount of energy. An emerging challenge is the development of ``environmentally friendly'' systems that are not only efficient in terms of time, but also energy efficient. In this poster, we outline our initial efforts at developing greener filtering systems by employing Field Programmable Gate Arrays (FPGA) to perform the core information processing task. FPGAs enable code to be executed in parallel at a chip level, while consuming only a fraction of the power of a standard (von Neuman style) processor. On a number of test collections, we demonstrate that the FPGA filtering system performs 10-20 times faster than ...
With the advent of big data and cloud computing, there is tremendous interest in optimised algorithm...
Power flow computation is ubiquitous in the operation and planning of power systems.\ud Traditional ...
Emerging data-centric workloads that operate on and harvest useful insights from large amounts of un...
Processing large volumes of information generally requires massive amounts of computational power, w...
With the rise in the amount information of being streamed across networks, there is a growing demand...
High speed real time video processing puts a lot of demand on hardware and Field Programmable Gate A...
Both computational performances and energy efficiency are required for the development of any mobile...
Both computational performances and energy efficiency are required for the development of any mobile...
Power consumption in data centres is a growing issue as the cost of the power for computation and co...
Power consumption in data centres is a growing issue as the cost of the power for computation and co...
In recent years, the field of high-performance computing has been facing a new challenge: achieving ...
Abstract—Median filters are a popular method for noise ex-traction, with much work done in the commu...
This article presents an approach for mapping real-time applications based on particle filters (PFs)...
Field programmable gate array (FPGA) processing units present considerably higher programming flexib...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
With the advent of big data and cloud computing, there is tremendous interest in optimised algorithm...
Power flow computation is ubiquitous in the operation and planning of power systems.\ud Traditional ...
Emerging data-centric workloads that operate on and harvest useful insights from large amounts of un...
Processing large volumes of information generally requires massive amounts of computational power, w...
With the rise in the amount information of being streamed across networks, there is a growing demand...
High speed real time video processing puts a lot of demand on hardware and Field Programmable Gate A...
Both computational performances and energy efficiency are required for the development of any mobile...
Both computational performances and energy efficiency are required for the development of any mobile...
Power consumption in data centres is a growing issue as the cost of the power for computation and co...
Power consumption in data centres is a growing issue as the cost of the power for computation and co...
In recent years, the field of high-performance computing has been facing a new challenge: achieving ...
Abstract—Median filters are a popular method for noise ex-traction, with much work done in the commu...
This article presents an approach for mapping real-time applications based on particle filters (PFs)...
Field programmable gate array (FPGA) processing units present considerably higher programming flexib...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
With the advent of big data and cloud computing, there is tremendous interest in optimised algorithm...
Power flow computation is ubiquitous in the operation and planning of power systems.\ud Traditional ...
Emerging data-centric workloads that operate on and harvest useful insights from large amounts of un...