2022
Authors
Macedo, R; Tanimura, Y; Haga, J; Chidarnbaram, V; Pereira, J; Paulo, J;
Publication
PROCEEDINGS OF THE 20TH USENIX CONFERENCE ON FILE AND STORAGE TECHNOLOGIES, FAST 2022
Abstract
We present PAID, a framework that allows developers to implement portable I/O policies and optimizations for different applications with minor modifications to their original code base. The chief insight behind PALO is that if we are able to intercept and differentiate requests as they flow through different layers of the I/O stack, we can enforce complex storage policies without significantly changing the layers themselves. PAIO adopts ideas from the Software-Defined Storage community, building data plane stages that mediate and optimize I/O requests across layers and a control plane that coordinates and fine-tunes stages according to different storage policies. We demonstrate the performance and applicability of PALO with two use cases. The first improves 99th percentile latency by 4 x in industry-standard LSM-based key-value stores. The second ensures dynamic per-application bandwidth guarantees under shared storage environments.
2022
Authors
Bashford Rogers, T; Santos, LP; Marnerides, D; Debattista, K;
Publication
ACM TRANSACTIONS ON GRAPHICS
Abstract
This article proposes a Markov Chain Monte Carlo (MCMC) rendering algorithm based on a family of guided transition kernels. The kernels exploit properties of ensembles of light transport paths, which are distributed according to the lighting in the scene, and utilize this information to make informed decisions for guiding local path sampling. Critically, our approach does not require caching distributions in world space, saving time and memory, yet it is able to make guided sampling decisions based on whole paths. We show how this can be implemented efficiently by organizing the paths in each ensemble and designing transition kernels for MCMC rendering based on a carefully chosen subset of paths from the ensemble. This algorithm is easy to parallelize and leads to improvements in variance when rendering a variety of scenes.
2022
Authors
Macedo, R; Miranda, M; Tanimura, Y; Haga, J; Ruhela, A; Harrell, SL; Evans, RT; Paulo, J;
Publication
2022 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER 2022)
Abstract
Modern large-scale I/O applications that run on HPC infrastructures are increasingly becoming metadata-intensive. Unfortunately, having multiple concurrent applications submitting massive amounts of metadata operations can easily saturate the shared parallel file system's metadata resources, leading to unresponsiveness of the storage backend and overall performance degradation. To address these challenges, we present PADLL, a storage middleware that enables system administrators to proactively control and ensure QoS over metadata workflows in HPC storage systems. We demonstrate its performance and feasibility by controlling the rate of both synthetic and realistic I/O workloads. Results show that PADLL can dynamically control metadata-aggressive workloads, prevent I/O burstiness, and ensure I/O fairness and prioritization.
2022
Authors
Rodrigues, N; Mendes, D; Santos, LP; Bouatouch, K;
Publication
COMPUTERS & GRAPHICS-UK
Abstract
2022
Authors
Maciel, A; Castro, JA; Ribeiro, C; Almada, M; Midão, L;
Publication
Int. J. Digit. Curation
Abstract
2022
Authors
Cassola, F; Mendes, D; Pinto, M; Morgado, L; Costa, S; Anjos, L; Marques, D; Rosa, F; Maia, A; Tavares, H; Coelho, A; Paredes, H;
Publication
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES
Abstract
The use of virtual reality (VR) for industrial training helps minimize risks and costs by allowing more frequent and varied use of experiential learning activities, leading to active and improved learning. However, creating VR training experiences is costly and time-consuming, requiring software development experts. Additionally, current authoring tools lack integration with existing data and are desktop-oriented, which detach the pedagogic process of creating the immersive experience from experiencing it in a situated context. In this article, we present a novel interactive approach for immersive authoring of VR-based experiential training by the trainers themselves, from inside the virtual environment and without the support of development experts. The design includes identifying interactable elements, such as 3-D models, equipment, tools, settings, and environment. The trainer also specifies by demonstration the actions to be performed by trainees, as a virtual choreography. During course execution, trainees' activities are also registered as virtual choreographies and matched to those specified by the trainer. Thus, trainer and trainee are culturally situated within their area semantics and social discourse, rather than adopting concepts of the VR system for the learning content. We conducted a usability case study with professionals from an international wind energy company, using detailed models of wind turbines and real-world procedures. Trainers set up a training course using the immersive authoring tool, and trainees executed the course. The learning experience and usability were analyzed, and the training was certified by comparing real-world task completion between a user who had undergone virtual training and a user who did not.
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