24,374 research outputs found
Orcc's Compa-Backend demonstration
International audienceThis paper presents the implementation of a video decoding application starting from its dataflow and CAL representations. Our objective is to demonstrate the ability of the Open RVC-CAL Compiler (Orcc) to generate code for embedded systems. For the demonstration, the video application will be an MPEG-4 Part2 decoder. The targeted architecture is a multi-core heterogeneous system deployed onto the Zynq platform from Xilinx
Systematic analysis of the decoding delay in multiview video
We present a framework for the analysis of the decoding delay in multiview video coding (MVC). We show that in real-time applications, an accurate estimation of the decoding delay is essential to achieve a minimum communication latency. As opposed to single-view codecs, the complexity of the multiview prediction structure and the parallel decoding of several views requires a systematic analysis of this decoding delay, which we solve using graph theory and a model of the decoder hardware architecture. Our framework assumes a decoder implementation in general purpose multi-core processors with multi-threading capabilities. For this hardware model, we show that frame processing times depend on the computational load of the decoder and we provide an iterative algorithm to compute jointly frame processing times and decoding delay. Finally, we show that decoding delay analysis can be applied to design decoders with the objective of minimizing the communication latency of the MVC system
A Computationally Efficient Neural Video Compression Accelerator Based on a Sparse CNN-Transformer Hybrid Network
Video compression is widely used in digital television, surveillance systems,
and virtual reality. Real-time video decoding is crucial in practical
scenarios. Recently, neural video compression (NVC) combines traditional coding
with deep learning, achieving impressive compression efficiency. Nevertheless,
the NVC models involve high computational costs and complex memory access
patterns, challenging real-time hardware implementations. To relieve this
burden, we propose an algorithm and hardware co-design framework named NVCA for
video decoding on resource-limited devices. Firstly, a CNN-Transformer hybrid
network is developed to improve compression performance by capturing
multi-scale non-local features. In addition, we propose a fast algorithm-based
sparse strategy that leverages the dual advantages of pruning and fast
algorithms, sufficiently reducing computational complexity while maintaining
video compression efficiency. Secondly, a reconfigurable sparse computing core
is designed to flexibly support sparse convolutions and deconvolutions based on
the fast algorithm-based sparse strategy. Furthermore, a novel heterogeneous
layer chaining dataflow is incorporated to reduce off-chip memory traffic
stemming from extensive inter-frame motion and residual information. Thirdly,
the overall architecture of NVCA is designed and synthesized in TSMC 28nm CMOS
technology. Extensive experiments demonstrate that our design provides superior
coding quality and up to 22.7x decoding speed improvements over other video
compression designs. Meanwhile, our design achieves up to 2.2x improvements in
energy efficiency compared to prior accelerators.Comment: Accepted by DATE 202
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the
demand for higher resolution, multi-view and large-scale multicast video
services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a
number of new opportunities for optimizing video delivery across both 5G core
and radio access networks. One of the promising approaches for video quality
adaptation, throughput enhancement and erasure protection is the use of
packet-level random linear network coding (RLNC). In this review paper, we
discuss the integration of RLNC into the 5G NR standard, building upon the
ideas and opportunities identified in 4G LTE. We explicitly identify and
discuss in detail novel 5G NR features that provide support for RLNC-based
video delivery in 5G, thus pointing out to the promising avenues for future
research.Comment: Invited paper for Special Issue "Network and Rateless Coding for
Video Streaming" - MDPI Informatio
DyPS: Dynamic Processor Switching for Energy-Aware Video Decoding on Multi-core SoCs
In addition to General Purpose Processors (GPP), Multicore SoCs equipping
modern mobile devices contain specialized Digital Signal Processor designed
with the aim to provide better performance and low energy consumption
properties. However, the experimental measurements we have achieved revealed
that system overhead, in case of DSP video decoding, causes drastic
performances drop and energy efficiency as compared to the GPP decoding. This
paper describes DyPS, a new approach for energy-aware processor switching (GPP
or DSP) according to the video quality . We show the pertinence of our solution
in the context of adaptive video decoding and describe an implementation on an
embedded Linux operating system with the help of the GStreamer framework. A
simple case study showed that DyPS achieves 30% energy saving while sustaining
the decoding performanc
Invited Abstract: A Simulation Package for Energy Consumption of Content Delivery Networks (CDNs)
Content Delivery Networks (CDNs) are becoming an integral part of the future
generation Internet. Traditionally, these networks have been designed with the
goals of traffic offload and the improvement of users' quality of experience
(QoE), but the energy consumption is also becoming an indispensable design
factor for CDNs to be a sustainable solution. To study and improve the CDN
architectures using this new design metric, we are planning to develop a
generic and flexible simulation package in OMNet++. This package is aimed to
render a holistic view about the CDN energy consumption behaviour by
incorporating the state-of-the-art energy consumption models proposed for the
individual elements of CDNs (e.g. servers, routers, wired and wireless links,
wireless devices, etc.) and for the various Internet contents (web pages,
files, streaming video, etc.).Comment: Published in: A. F\"orster, C. Minkenberg, G. R. Herrera, M. Kirsche
(Eds.), Proc. of the 2nd OMNeT++ Community Summit, IBM Research - Zurich,
Switzerland, September 3-4, 2015, arXiv:1509.03284, 201
Reliable Video Streaming over mmWave with Multi Connectivity and Network Coding
The next generation of multimedia applications will require the
telecommunication networks to support a higher bitrate than today, in order to
deliver virtual reality and ultra-high quality video content to the users. Most
of the video content will be accessed from mobile devices, prompting the
provision of very high data rates by next generation (5G) cellular networks. A
possible enabler in this regard is communication at mmWave frequencies, given
the vast amount of available spectrum that can be allocated to mobile users;
however, the harsh propagation environment at such high frequencies makes it
hard to provide a reliable service. This paper presents a reliable video
streaming architecture for mmWave networks, based on multi connectivity and
network coding, and evaluates its performance using a novel combination of the
ns-3 mmWave module, real video traces and the network coding library Kodo. The
results show that it is indeed possible to reliably stream video over cellular
mmWave links, while the combination of multi connectivity and network coding
can support high video quality with low latency.Comment: To be presented at the 2018 IEEE International Conference on
Computing, Networking and Communications (ICNC), March 2018, Maui, Hawaii,
USA (invited paper). 6 pages, 4 figure
Moving Multimedia Simulations into the Cloud: a Cost-Effective Solution
Researchers often demand bursts of computing power to quickly obtain the results of certain simulation activities. Multimedia communication simulations usually belong to such category. They may require several days on a generic PC to test a comprehensive set of conditions depending on the complexity of the scenario. This paper proposes to use a cloud computing framework to accelerate these simulations and, consequently, research activities, while at the same time reducing the overall costs. A practical simulation example is shown, representative of a typical simulation of H.264/AVC video communications over a wireless channel. This work shows that, by means of a commercial cloud computing provider, the gains of the proposed technique compared to more traditional solutions using dedicated computers can be significant in terms of speed and cost reductio
- âŠ