30,270 research outputs found
Optimizing Frameworks Performance Using C++ Modules Aware ROOT
ROOT is a data analysis framework broadly used in and outside of High Energy
Physics (HEP). Since HEP software frameworks always strive for performance
improvements, ROOT was extended with experimental support of runtime C++
Modules. C++ Modules are designed to improve the performance of C++ code
parsing. C++ Modules offers a promising way to improve ROOT's runtime
performance by saving the C++ header parsing time which happens during ROOT
runtime. This paper presents the results and challenges of integrating C++
Modules into ROOT.Comment: 8 pages, 3 figures, 6 listing, CHEP 2018 - 23rd International
Conference on Computing in High Energy and Nuclear Physic
Optimum graph cuts for pruning binary partition trees of polarimetric SAR images
This paper investigates several optimum graph-cut techniques for pruning binary partition trees (BPTs) and their usefulness for the low-level processing of polarimetric synthetic aperture radar (PolSAR) images. BPTs group pixels to form homogeneous regions, which are hierarchically structured by inclusion in a binary tree. They provide multiple resolutions of description and easy access to subsets of regions. Once constructed, BPTs can be used for a large number of applications. Many of these applications consist in populating the tree with a specific feature and in applying a graph cut called pruning to extract a partition of the space. In this paper, different pruning examples involving the optimization of a global criterion are discussed and analyzed in the context of PolSAR images for segmentation. Through the objective evaluation of the resulting partitions by means of precision-and-recall-for-boundaries curves, the best pruning technique is identified, and the influence of the tree construction on the performances is assessed.Peer ReviewedPostprint (author's final draft
Interactive Co-Design of Form and Function for Legged Robots using the Adjoint Method
Our goal is to make robotics more accessible to casual users by reducing the
domain knowledge required in designing and building robots. Towards this goal,
we present an interactive computational design system that enables users to
design legged robots with desired morphologies and behaviors by specifying
higher level descriptions. The core of our method is a design optimization
technique that reasons about the structure, and motion of a robot in coupled
manner in order to achieve user-specified robot behavior, and performance. We
are inspired by the recent works that also aim to jointly optimize robot's form
and function. However, through efficient computation of necessary design
changes, our approach enables us to keep user-in-the-loop for interactive
applications. We evaluate our system in simulation by automatically improving
robot designs for multiple scenarios. Starting with initial user designs that
are physically infeasible or inadequate to perform the user-desired task, we
show optimized designs that achieve user-specifications, all while ensuring an
interactive design flow.Comment: 8 pages; added link of the accompanying vide
The Power of Asymmetry in Binary Hashing
When approximating binary similarity using the hamming distance between short
binary hashes, we show that even if the similarity is symmetric, we can have
shorter and more accurate hashes by using two distinct code maps. I.e. by
approximating the similarity between and as the hamming distance
between and , for two distinct binary codes , rather than as
the hamming distance between and .Comment: Accepted to NIPS 2013, 9 pages, 5 figure
Evolving SDN for Low-Power IoT Networks
Software Defined Networking (SDN) offers a flexible and scalable architecture
that abstracts decision making away from individual devices and provides a
programmable network platform. However, implementing a centralized SDN
architecture within the constraints of a low-power wireless network faces
considerable challenges. Not only is controller traffic subject to jitter due
to unreliable links and network contention, but the overhead generated by SDN
can severely affect the performance of other traffic. This paper addresses the
challenge of bringing high-overhead SDN architecture to IEEE 802.15.4 networks.
We explore how traditional SDN needs to evolve in order to overcome the
constraints of low-power wireless networks, and discuss protocol and
architectural optimizations necessary to reduce SDN control overhead - the main
barrier to successful implementation. We argue that interoperability with the
existing protocol stack is necessary to provide a platform for controller
discovery and coexistence with legacy networks. We consequently introduce
{\mu}SDN, a lightweight SDN framework for Contiki, with both IPv6 and
underlying routing protocol interoperability, as well as optimizing a number of
elements within the SDN architecture to reduce control overhead to practical
levels. We evaluate {\mu}SDN in terms of latency, energy, and packet delivery.
Through this evaluation we show how the cost of SDN control overhead (both
bootstrapping and management) can be reduced to a point where comparable
performance and scalability is achieved against an IEEE 802.15.4-2012 RPL-based
network. Additionally, we demonstrate {\mu}SDN through simulation: providing a
use-case where the SDN configurability can be used to provide Quality of
Service (QoS) for critical network flows experiencing interference, and we
achieve considerable reductions in delay and jitter in comparison to a scenario
without SDN
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