This session features papers focusing on imageprocessing algorithms, self-learning reconfiguration management and fault tolerance for reconfigurable systems.
This session features papers focusing on imageprocessing algorithms, self-learning reconfiguration management and fault tolerance for reconfigurable systems.
The GPU session presents research papers describing ongoing research, exciting new research projects, and encouraging preliminary results. This session provides an excellent opportunity to share and discuss ideas and ...
The GPU session presents research papers describing ongoing research, exciting new research projects, and encouraging preliminary results. This session provides an excellent opportunity to share and discuss ideas and latest research results with colleagues working on GPU. The papers accepted describe novel or interesting research topics in parallel computing and applications of GPU computing and OpenCL/CUDA to diverse problems in image and signalprocessing domain.
This session presents a flexible VLIW processor, an operating system API for handling hardware tasks, and a performance comparison of CPU, GPU and FPGA using an image reconstruction algorithm.
This session presents a flexible VLIW processor, an operating system API for handling hardware tasks, and a performance comparison of CPU, GPU and FPGA using an image reconstruction algorithm.
This session presents several experiences in the processor design domain for signalprocessing. The signalprocessing algorithms must generally support real hard real time constraints, and in this context the executio...
This session presents several experiences in the processor design domain for signalprocessing. The signalprocessing algorithms must generally support real hard real time constraints, and in this context the execution resources need to be very efficient. designing specific processors or specific dedicated architectures is then a good issue to ensure the performances. Several specific architectures are presented in the following papers, and the authors present the result obtained and compare them with other solutions.
Low power technologies for VLSI allows tightly coupled complex processing parts near video sensors, making so-called smart sensors. They can be miniaturized for semi-automatic in vivo human body exploration. However s...
Low power technologies for VLSI allows tightly coupled complex processing parts near video sensors, making so-called smart sensors. They can be miniaturized for semi-automatic in vivo human body exploration. However smart sensors designs are more and more complexes to be simulated using traditional methods, new approaches are now emerging.
Being able to estimate power and energy consumptions at high level in embedded systems design flows is crucial for nowadays complex applications and systems where low level approaches are not usable. Early estimates, ...
Being able to estimate power and energy consumptions at high level in embedded systems design flows is crucial for nowadays complex applications and systems where low level approaches are not usable. Early estimates, when good, naturally lead to decisive optimization opportunities. The session will discuss two important points in this context: the modeling of operating systems energy overhead and the refinement of behavior analysis for power estimation.
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