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Welzl, Michael; Oepen, Stephan; Cezary Jaskula, Cezary; Griwodz, Carsten & Islam, Safiqul
(2021).
Collaboration in the IETF: an initial analysis of two decades in email discussions.
Computer communication review.
ISSN 0146-4833.
51(3),
p. 29–32.
doi:
10.1145/3477482.3477488.
Show summary
RFC 9000, published in May 2021, marks an important milestone for the Internet's standardization body, the Internet Engineering Task Force (IETF): finally, the specification of the QUIC protocol is available. QUIC is the result of a five-year effort - and it is also the second of two major protocols (the first being SPDY, which later became HTTP/2) that Google LLC first deployed, and then brought to the IETF for standardization. This begs the question: when big players follow such a "shoot first, discuss later" approach, is IETF collaboration still "real", or is the IETF now being (mis-)used to approve protocols for standardization when they are already practically established, without really actively involving anyone but the main proponents?
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Boulet-Gilly, Edmond; Morin, Géraldine; Griwodz, Carsten & Gasparini, Simone
(2019).
Room modeling:Encoding Point Cloudinto a piecewise planar model and heightmaps.
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Midoglu, Cise; Klausen, Magnus; Alay Erduran, Özgü; Yazidi, Anis; Haugerud, Hårek & Griwodz, Carsten
(2019).
Poster: QoE-Based Analysis of Real-Time Adaptive 360-Degree Video Streaming.
In Dasari, Mallesham; Soltanaghaei, Elahe & Yeh, Chia-Yi (Ed.),
S3'19: Proceedings of the 2019 on Wireless of the Students, by the Students, and for the Students Workshop.
Association for Computing Machinery (ACM).
ISSN 9781450369299.
doi:
10.1145/3349621.3355728.
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Borgli, Rune Johan; Pogorelov, Konstantin; Riegler, Michael; Markussen, Jonas Sæther; Stensland, Håkon Kvale & Halvorsen, Pål
[Show all 9 contributors for this article]
(2019).
Efficient Processing of Medical Videos in a Multi-auditory Environment Using Gpu Lending.
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Pogorelov, Konstantin; Ostroukhova, Olga; Jeppsson, Mattis; Espeland, Håvard; Griwodz, Carsten & de Lange, Thomas
[Show all 9 contributors for this article]
(2018).
Deep Learning and Hand-Crafted Feature Based Approaches for Polyp Detection in Medical Videos.
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Pogorelov, Konstantin; Ostroukhova, Olga; Petlund, Andreas; Halvorsen, Pål; de Lange, Thomas & Espeland, Håvard
[Show all 9 contributors for this article]
(2018).
Deep Learning and Handcrafted Feature Based Approaches for Automatic Detection of Angiectasia.
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Pogorelov, Konstantin; Randel, Kristin Ranheim; de Lange, Thomas; Eskeland, Sigrun Losada; Griwodz, Carsten & Johansen, Dag
[Show all 12 contributors for this article]
(2017).
Nerthus: A Bowel Preparation Quality Video Dataset.
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Pogorelov, Konstantin; Eskeland, Sigrun Losada; de Lange, Thomas; Griwodz, Carsten; Randel, Kristin Ranheim & Stensland, Håkon Kvale
[Show all 11 contributors for this article]
(2017).
A Holistic Multimedia System for Gastrointestinal Tract Disease Detection.
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Pogorelov, Konstantin; Randel, Kristin Ranheim; Griwodz, Carsten; Eskeland, Sigrun Losada; de Lange, Thomas & Johansen, Dag
[Show all 12 contributors for this article]
(2017).
KVASIR: A Multi-Class Image Dataset for Computer Aided Gastrointestinal Disease Detection.
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Stokke, Kristoffer Robin; Stensland, Håkon Kvale; Halvorsen, Pål & Griwodz, Carsten
(2016).
A High Precision Power Model for the Tegra K1 CPU, GPU and RAM".
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Pogorelov, Konstantin; Riegler, Michael; Halvorsen, Pål & Griwodz, Carsten
(2016).
Simula @ MediaEval 2016 Context of Experience Task.
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Riegler, Michael; SPAMPINATO, CONCETTO; Larson, Martha; Griwodz, Carsten & Halvorsen, Pål
(2016).
The MediaEval 2016 Context of Experience Task: Recommending Videos Suiting a Watching Situation.
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Riegler, Michael; Lux, Mathias; Griwodz, Carsten; SPAMPINATO, CONCETTO; de Lange, Thomas & Eskeland, Sigrun Losada
[Show all 13 contributors for this article]
(2016).
Multimedia and Medicine: Teammates for Better Disease Detection and Survival.
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Stokke, Kristoffer Robin; Stensland, Håkon Kvale; Griwodz, Carsten & Halvorsen, Pål
(2016).
A high-precision, hybrid GPU, CPU and RAM power model for generic multimedia workloads.
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Winther, Bård; Riegler, Michael; Calvet, Lilian; Griwodz, Carsten & Halvorsen, Pål
(2016).
Why Design Matters - Crowdsourcing of Complex Tasks.
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Dwarakanath, Deepak; Griwodz, Carsten; Halvorsen, Pål & Llldballe, Jacob
(2015).
Online Re-calibration for Robust 3D Measurement Using Single Camera-PantoInspect Train Monitoring System
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Riegler, Michael; Eg, Ragnhild; Calvet, Lilian; Halvorsen, Pål & Griwodz, Carsten
(2015).
Playing Around the Eye Tracker - A Serious Game Based Dataset.
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Riegler, Michael; Calvet, Lilian; Calvet, Amandine; Halvorsen, Pål & Griwodz, Carsten
(2015).
Exploitation of Producer Intent in Relation to Bandwidth and QoE for Online Video Streaming Services
.
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Gaddam, Vamsidhar Reddy; Ngo, Hoang Bao; Langseth, Ragnar; Griwodz, Carsten; Johansen, Dag & Halvorsen, Pål
(2015).
Tiling of Panorama Video for Interactive Virtual Cameras: Overheads and Potential Bandwidth Requirement Reduction.
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Riegler, Michael; Larson, Martha; SPAMPINATO, CONCETTO; Markussen, Jonas; Halvorsen, Pål & Griwodz, Carsten
(2015).
Introduction to a Task on Context of Experience: Recommending Videos Suiting a Watching Situation.
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Albisser, Zeno; Riegler, Michael; Halvorsen, Pål; Zhou, Jiang; Griwodz, Carsten & Balasingham, Ilangko
[Show all 7 contributors for this article]
(2015).
Expert Driven Semi-Supervised Elucidation Tool for Medical Endoscopic Videos.
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Olsen, Preben Nenseth; Nyhus, Martin; Halvorsen, Pål & Griwodz, Carsten
(2015).
A Logical Memory Model for Scaling Parallel Multimedia Workloads.
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Stensland, Håkon Kvale; Halvorsen, Pål & Griwodz, Carsten
(2015).
Processing Multimedia Workloads on Heterogeneous Multicore Architectures.
Akademika Publishing.
ISSN 1501-7710.
Full text in Research Archive
Show summary
Processor architectures have been evolving quickly since the introduction of the central processing unit. For a very long time, one of the important means of increasing per- formance was to increase the clock frequency. However, in the last decade, processor manufacturers have hit the so-called power wall, with high heat dissipation. To overcome this problem, processors were designed with reduced clock frequencies but with multiple cores and, later, heterogeneous processing elements. This shift introduced a new challenge for programmers: Legacy applications, written without parallelization in mind, gain no benefits from moving to multicore and heterogeneous architectures. Another challenge for the programmers is that heterogeneous architecture designs are very different with respect to caches, memory types, execution unit organization, and so forth and, in the worst case, a programmer must completely rewrite the application to obtain the best performance on the new architecture.
Multimedia workloads, such as video encoding, are often time sensitive and interac- tive. These workloads differ from traditional batch processing workloads with no real-time requirements. This work investigates how to use modern heterogeneous architectures ef- ficiently to process multimedia workloads. To do so, we investigate both simple and complex workloads on multiple architectures to learn about the properties of these archi- tectures. When programing multimedia workloads, it is very important to know how the algorithms perform on the target architecture. In addition, achieving high performance on heterogeneous architectures is not a trivial task, often requiring detailed knowledge about the architecture. We therefore evaluate several optimizations so we can learn how best to write programs for these architectures and avoid potential pitfalls. We later use the knowledge gained to propose a framework design and language called Parallel Pro- cessing Graph (P2G). The P2G framework is designed for multimedia workloads and supports heterogeneous architectures. To demonstrate the feasibility of the framework, we construct a proof-of-concept implementation. Two simple workloads show that we can express multimedia workloads in the system. We also demonstrate the scalability of the designed solution.