International audienceThe pseudo-log image transform belongs to a class of image processing kernels that generate memory references which are nonlinear functions of loop indices. Due to the nonlinearity of the memory references, the usual design methodologies do not allow efficient hardware implementation for nonlinear kernels. For optimized hardware implementation, these kernels require the creation of a customized memory hierarchy and efficient data/memory management strategy. We present the design and real-time hardware implementation of a pseudo-log image transform IP (hardware image processing engine) using a memory management framework. The framework generates a controller which efficiently manages input data movement in the form of t...
Hardware accelerators in heterogeneous multiprocessor system-on-chips are becoming popular as a mean...
With the increasing capacity in today's hardware system design enabled by technology scaling, image ...
International audienceThe wide landscape of memory-hungry and compute-intensive Convolutional Neural...
ISBN : 978-08-19-494-290International audienceThe pseudo-log image transform is essentially a logari...
ISBN 978-3-9810801-8-6International audienceModern High Level Synthesis (HLS) tools are now efficien...
With increasing FPGA chip density, it is possible to implement more sophisticated algorithms on FPGA...
Modern embedded systems for DSP applications are increasingly being implemented on heterogeneous pro...
High-level synthesis (HLS) and register transfer level (RTL) are two popular methods to design FPGAs...
Multimedia applications are examples of a class of algorithms that are both calculation and data int...
International audienceConvolutional Neural Networks (CNNs) have emerged as an answer to next-generat...
When implementing multimedia applications, solutions in dedicated hardware are chosen only when the ...
Memory is the biggest limiting factor to the widespread use of FPGAs for high-level image processing...
This paper discusses a method of hardware synthesis for re-configurable heterogeneous pipelined acce...
Some data- and compute-intensive applications can be ac-celerated by offloading portions of codes to...
In modern embedded systems, heterogeneous architectures are crucial in achieving desired performance...
Hardware accelerators in heterogeneous multiprocessor system-on-chips are becoming popular as a mean...
With the increasing capacity in today's hardware system design enabled by technology scaling, image ...
International audienceThe wide landscape of memory-hungry and compute-intensive Convolutional Neural...
ISBN : 978-08-19-494-290International audienceThe pseudo-log image transform is essentially a logari...
ISBN 978-3-9810801-8-6International audienceModern High Level Synthesis (HLS) tools are now efficien...
With increasing FPGA chip density, it is possible to implement more sophisticated algorithms on FPGA...
Modern embedded systems for DSP applications are increasingly being implemented on heterogeneous pro...
High-level synthesis (HLS) and register transfer level (RTL) are two popular methods to design FPGAs...
Multimedia applications are examples of a class of algorithms that are both calculation and data int...
International audienceConvolutional Neural Networks (CNNs) have emerged as an answer to next-generat...
When implementing multimedia applications, solutions in dedicated hardware are chosen only when the ...
Memory is the biggest limiting factor to the widespread use of FPGAs for high-level image processing...
This paper discusses a method of hardware synthesis for re-configurable heterogeneous pipelined acce...
Some data- and compute-intensive applications can be ac-celerated by offloading portions of codes to...
In modern embedded systems, heterogeneous architectures are crucial in achieving desired performance...
Hardware accelerators in heterogeneous multiprocessor system-on-chips are becoming popular as a mean...
With the increasing capacity in today's hardware system design enabled by technology scaling, image ...
International audienceThe wide landscape of memory-hungry and compute-intensive Convolutional Neural...