5,610 research outputs found
LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing
LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft
Neuromorphic Approach Sensitivity Cell Modeling and FPGA Implementation
Neuromorphic engineering takes inspiration from biology to
solve engineering problems using the organizing principles of biological
neural computation. This field has demonstrated success in sensor based
applications (vision and audition) as well in cognition and actuators.
This paper is focused on mimicking an interesting functionality of the
retina that is computed by one type of Retinal Ganglion Cell (RGC).
It is the early detection of approaching (expanding) dark objects. This
paper presents the software and hardware logic FPGA implementation
of this approach sensitivity cell. It can be used in later cognition layers as
an attention mechanism. The input of this hardware modeled cell comes
from an asynchronous spiking Dynamic Vision Sensor, which leads to an
end-to-end event based processing system. The software model has been
developed in Java, and computed with an average processing time per
event of 370 ns on a NUC embedded computer. The output firing rate
for an approaching object depends on the cell parameters that represent
the needed number of input events to reach the firing threshold. For the
hardware implementation on a Spartan6 FPGA, the processing time is
reduced to 160 ns/event with the clock running at 50 MHz.Ministerio de EconomĂa y Competitividad TEC2016-77785-PUniĂłn Europea FP7-ICT-60095
Digital signal processing: the impact of convergence on education, society and design flow
Design and development of real-time, memory and processor hungry digital signal processing systems has for decades been accomplished on general-purpose microprocessors. Increasing needs for high-performance DSP systems made these microprocessors unattractive for such implementations. Various attempts to improve the performance of these systems resulted in the use of dedicated digital signal processing devices like DSP processors and the former heavyweight champion of electronics design â Application Specific Integrated Circuits.
The advent of RAM-based Field Programmable Gate Arrays has changed the DSP design flow. Software algorithmic designers can now take their DSP algorithms right from inception to hardware implementation, thanks to the increasing availability of software/hardware design flow or hardware/software co-design. This has led to a demand in the industry for graduates with good skills in both Electrical Engineering and Computer Science. This paper evaluates the impact of technology on DSP-based designs, hardware design languages, and how graduate/undergraduate courses have changed to suit this transition
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