Hardware acceleration of network functions is essential to meet the challenging Quality of Service requirements in nowadays computer networks. Graphical Processing Units (GPU) are a widely deployed technology that can also be used for computing tasks, including acceleration of network functions. In this work, we demonstrate how commodity GPUs, which do not provide any network interfaces, can be used to accelerate network functions. Our approach leverages PCIe peer-to-peer capabilities and allows the GPU to control the network interface card directly, without any assistance from the operating system or control application. The presented evaluation results demonstrate the feasibility of our approach and its performance of up to 10 Gbit/s, even for small packets.

The large variety of compute-heavy and data-driven applications accelerate the need for a distributed I/O solution that enables cost-effective scaling of resources between networked hosts. For example, in a cluster system, different machines may have various devices available at different times, but moving workloads to remote units over the network is often costly and introduces large overheads compared to accessing local resources. To facilitate I/O disaggregation and device sharing among hosts connected using Peripheral Component Interconnect Express (PCIe) non-transparent bridges, we present SmartIO. NVMes, GPUs, network adapters, or any other standard PCIe device may be borrowed and accessed directly, as if they were local to the remote machines. We provide capabilities beyond existing disaggregation solutions by combining traditional I/O with distributed shared-memory functionality, allowing devices to become part of the same global address space as cluster applications. Software is entirely removed from the data path, and simultaneous sharing of a device among application processes running on remote hosts is enabled. Our experimental results show that I/O devices can be shared with remote hosts, achieving native PCIe performance. Thus, compared to existing device distribution mechanisms, SmartIO provides more efficient, low-cost resource sharing, increasing the overall system performance.

In this paper, we present a demo that utilizes Device Lending via PCI Express (PCIe) in the context of a multi-auditory environment. Device Lending is a transparent, low-latency cross-machine PCIe device sharing mechanism without any the need for implementing application-specific distribution mechanisms. As workload, we use a computer-aided diagnosis system that is used to automatically find polyps and mark them for medical doctors during a colonoscopy. We choose this scenario because one of the main requirements is to perform the analysis in real-time. The demonstration consists of a setup of two computers that demonstrates how Device Lending can be used to improve performance, as well as its effect of providing the performance needed for real-time feedback. We also present a performance evaluation that shows its real-time capabilities of it.

In this paper, we present the dataset Right Inflight developed to support the exploration of the match between video content and the situation in which that content is watched. Specifically, we look at videos that are suitable to be watched on an airplane, where the main assumption is that that viewers watch movies with the intent of relaxing themselves and letting time pass quickly, despite the inconvenience and discomfort of flight. The aim of the dataset is to support the development of recommender systems, as well as computer vision and multimedia retrieval algorithms capable of automatically predicting which videos are suitable for inflight consumption. Our ultimate goal is to promote a deeper understanding of how people experience video content, and of how technology can support people in finding or selecting video content that supports them in regulating their internal states in certain situations. Right Inflight consists of 318 human-annotated movies, for which we provide links to trailers, a set of pre-computed low-level visual, audio and text features as well as user ratings. The annotation was performed by crowdsourcing workers, who were asked to judge the appropriateness of movies for inflight consumption.

In this paper, we present the computer-aided diagnosis part of the EIR system [9], which can support medical experts in the task of detecting diseases and anatomical landmarks in the gastrointestinal (GI) system. This includes automatic detection of important findings in colonoscopy videos and marking them for the doctors. EIR is designed in a modular way so that it can easily be extended for other diseases. For this demonstration, we will focus on polyp detection, as our system is trained with the ASU-Mayo Clinic polyp database [5].

The challenge of scaling IO performance of multimedia systems to demands of their users has attracted much research. A lot of effort has gone into development of distributed systems that add little latency and computing overhead. For machines in PCI Express (PCIe) clusters, we propose Device Lending as a novel solution which works at a system level.

Time-dependent applications using TCP often send thin-stream traffic, characterised by small packets and high inter-transmission-times. Retransmissions after packet loss can result in very high delays for such flows as they often cannot trigger fast retransmit. Redundant Data Bundling is a mechanism that preempts the experience of loss for a flow by piggybacking unacknowledged segments with new data as long as the total packet size is lower than the flow maximum segment size. Although successful at reducing retransmission latency, this mechanism had design issues leaving it open for abuse, effectively making it unsuitable for general Internet deployment. In this paper, we have redesigned the RDB mechanism to make it safe for deployment. We improve the trigger for when to apply it and evaluate its fairness towards competing traffic. Extensive experimental results confirm that our proposed modifications allows for inter-flow fairness while maintaining the significant latency reductions from the original RDB mechanism.