Introduction to High Performance Computing at Case Western Reserve University
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Designing and Packaging Printer and Scanner Drivers
Designing and Packaging Printer and Scanner Drivers OpenPrinting MC on Linux Plumbers 2020 August 28, 2020 Till Kamppeter, OpenPrinting What we had ● Printer drivers – PPD files – Filters, perhaps also backends – All has to be in CUPS-specific directories ● Scanner drivers – Shared libraries with SANE ABI in SANE-specific directories ● Packaging – Binaries were built specific to destination distro and packaged in DEB or RPM packages – For each distro drivers need to be built, packaged, and tested separately – As files need to be in specific directories drivers cannot be installed with CUPS in a Snap or with scanning user applications in Snaps What we want ● Sandboxed packaging – Snaps – Distribution-independent: Install from Snap Store on any distro running snapd – More security: Every package with all its libraries and files in its own sandbox, fine-grained control for communication between packages – All-Snap distributions ● But – You cannot drop driver files into directories of a snapped CUPS or snapped user applications, Snaps do not see the system’s files – Snaps only communicate via IP or D-Bus, not by files ● Also – CUPS is deprecating support for PPD files, working by itself only in driverless IPP mode. The New Architecture ● Printer/Scanner Applications emulating an IPP device – Easily snappable: Communicates only via IP – Multi-function device support, Printing, Scanning, and Fax Out can be done in one Snap/Application – Web admin interface for vendor/device-specific GUI – Behaves like a network printer/scanner/multi-function -
The Interplay of Compile-Time and Run-Time Options for Performance Prediction Luc Lesoil, Mathieu Acher, Xhevahire Tërnava, Arnaud Blouin, Jean-Marc Jézéquel
The Interplay of Compile-time and Run-time Options for Performance Prediction Luc Lesoil, Mathieu Acher, Xhevahire Tërnava, Arnaud Blouin, Jean-Marc Jézéquel To cite this version: Luc Lesoil, Mathieu Acher, Xhevahire Tërnava, Arnaud Blouin, Jean-Marc Jézéquel. The Interplay of Compile-time and Run-time Options for Performance Prediction. SPLC 2021 - 25th ACM Inter- national Systems and Software Product Line Conference - Volume A, Sep 2021, Leicester, United Kingdom. pp.1-12, 10.1145/3461001.3471149. hal-03286127 HAL Id: hal-03286127 https://hal.archives-ouvertes.fr/hal-03286127 Submitted on 15 Jul 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. The Interplay of Compile-time and Run-time Options for Performance Prediction Luc Lesoil, Mathieu Acher, Xhevahire Tërnava, Arnaud Blouin, Jean-Marc Jézéquel Univ Rennes, INSA Rennes, CNRS, Inria, IRISA Rennes, France [email protected] ABSTRACT Both compile-time and run-time options can be configured to reach Many software projects are configurable through compile-time op- specific functional and performance goals. tions (e.g., using ./configure) and also through run-time options (e.g., Existing studies consider either compile-time or run-time op- command-line parameters, fed to the software at execution time). -
Accurate Segmentation of Brain MR Images
Accurate segmentation of brain MR images Master of Science Thesis in Biomedical Engineering ANTONIO REYES PORRAS PÉREZ Department of Signals and Systems Division of Biomedical Engineering CHALMERS UNIVERSITY OF TECHNOLOGY Göteborg, Sweden, 2010 Report No. EX028/2010 Abstract Full brain segmentation has been of significant interest throughout the years. Recently, many research groups worldwide have been looking into development of patient-specific electromagnetic models for dipole source location in EEG. To obtain this model, accurate segmentation of various tissues and sub-cortical structures is thus required. In this project, the performance of three of the most widely used software packages for brain segmentation has been analyzed: FSL, SPM and FreeSurfer. For the analysis, real images from a patient and a set of phantom images have been used in order to evaluate the performance r of each one of these tools. Keywords: dipole source location, brain, patient-specific model, image segmentation, FSL, SPM, FreeSurfer. Acknowledgements To my advisor, Antony, for his guidance through the project. To my partner, Koushyar, for all the days we have spent in the hospital helping each other. To the staff in Sahlgrenska hospital for their collaboration. To MedTech West for this opportunity to learn. Table of contents 1. Introduction ......................................................................................................................................... 1 2. Magnetic resonance imaging .............................................................................................................. -
Forensic Identification of Unique Kali Systems Through the Use of File Hashes and Names
Forensic Identification of Unique Kali Systems Through the Use of File Hashes and Names Troy Ward January 25, 2021 Troy Ward Table of Contents Introduction .................................................................................................................................................. 4 Kali Linux ....................................................................................................................................................... 4 Methodology ................................................................................................................................................. 4 Analysis ......................................................................................................................................................... 5 Unique Names ............................................................................................................................................... 6 Eth0.lease .................................................................................................................................................. 6 Font Config ................................................................................................................................................ 7 LightDM ..................................................................................................................................................... 8 System.Journal ......................................................................................................................................... -
Papermerge Documentation
Papermerge Feb 29, 2020 Contents 1 Requirements 3 1.1 Python..................................................3 1.2 Imagemagick...............................................3 1.3 Poppler..................................................3 1.4 Tesseract.................................................4 1.5 Database.................................................4 2 Installation 5 2.1 OS Specific Packages..........................................5 2.1.1 1. Web App + Workers Machine................................5 2.1.1.1 Ubuntu Bionic 18.04 (LTS)..............................5 2.1.2 2. Web App Machine......................................6 2.1.2.1 Ubuntu Bionic 18.04 (LTS)..............................6 2.1.3 3. Worker Machine.......................................6 2.2 Manual Way...............................................6 2.2.1 Package Dependencies.....................................6 2.2.2 Web App............................................7 2.2.3 Worker.............................................9 2.2.4 Recurring Commands...................................... 10 2.3 Systemd................................................. 11 2.3.1 Package Dependencies..................................... 11 2.3.2 Web App............................................ 11 2.4 Docker.................................................. 13 2.5 Ansible (Semiautomated)........................................ 13 2.6 Jenkins + Ansible (Fully Automated Deployment)........................... 14 3 Languages Support 15 4 REST API 17 4.1 How It Works?............................................. -
Freesurfer Tutorial
FreeSurfer Tutorial FreeSurfer is brought to you by the Martinos Center for Biomedical Imaging supported by NCRR/P41RR14075, Massachusetts General Hospital, Boston, MA USA 2008-06-01 20:47 1 FreeSurfer Tutorial Table of Contents Section Page Overview and course outline 3 Inspection of Freesurfer output 5 Troubleshooting your output 22 Fixing a bad skull strip 26 Making edits to the white matter 34 Correcting pial surfaces 46 Using control points to fix intensity normalization 50 Talairach registration 55 recon-all: morphometry and reconstruction 69 recon-all: process flow table 97 QDEC Group analysis 100 Group analysis: average subject, design matrix, mri_glmfit 125 Group analysis: visualization and inspection 149 Integrating FreeSurfer and FSL's FEAT 159 Exercise overview 172 Tkmedit reference 176 Tksurfer reference 211 Glossary 227 References 229 Acknowledgments 238 2008-06-01 20:47 2 top FreeSurfer Slides 1. Introduction to Freesurfer - Bruce Fischl 2. Anatomical Analysis with Freesurfer - Doug Greve 3. Surface-based Group Analysis - Doug Greve 4. Applying FreeSurfer Tools to FSL fMRI Analysis - Doug Greve FreeSurfer Tutorial Overview The FreeSurfer tools deal with two main types of data: volumetric data volumes of voxels and surface data polygons that tile a surface. This tutorial should familiarize you with FreeSurfer’s volume and surface processing streams, the recommended workflow to execute these, and many of their component tools. The tutorial also describes some of FreeSurfer's tools for registering volumetric datasets, performing group analysis on morphology data, and integrating FSL Feat output with FreeSurfer overlaying color coded parametric maps onto the cortical surface and visualizing plotted results. -
Confrontsred Tape
IPS: THE MENTAL HEALTH SERVICES CONFERENCE Oct. 8-11, 2015 • New York City When Good Care Confronts Red Tape Navigating the System for Our Patients and Our Practice New York, NY | Sheraton New York Times Square POSTER SESSION OCTOBER 09, 2015 POSTER SESSION 1 P1- 1 ANGIOEDEMA DUE TO POTENTIATING EFFECTS OF RITONIVIR ON RISPERIDONE: CASE REPORT Lead Author: Luisa S. Gonzalez, M.D. Co-Author(s): David A. Kasle MSIII Kavita Kothari M.D. SUMMARY: For many drugs, the liver is the principal site of its metabolism. The most important enzyme system of phase I metabolism is the cytochrome P-450 (CYP450). Ritonavir, a protease inhibitor used for the treatment of human immunodeficiency virus (HIV) infection and acquired immunodeficiency syndrome (AIDS), has been shown to be a potent inhibitor of the (CYP450) 3A and 2D6 isozymes. This inhibition increases the chance for potential drug-drug interactions with compounds that are metabolized by these isoforms. Risperidone, a second generation atypical antipsychotic, is metabolized to a significant extent by the (CYP450) 2D6, and to a lesser extent 3A4. Ritonavir and risperidone can both cause serious, and even life threatening, side effects. An example of one such rare side effect is angioedema which is characterized by edema of the deep dermal and subcutaneous tissues. Here we present three cases of patients residing in a nursing home setting, diagnosed with HIV/AIDS and comorbid psychiatric illness. These patients were all on antiretroviral medications such as ritonavir, and all later presented with varying degrees of edema after long term use of risperidone. We aim to bring to awareness the potential for ritonavir inhibiting the metabolism of risperidone, thus leading to an increased incidence of angioedema in these patients. -
Seed Selection for Successful Fuzzing
Seed Selection for Successful Fuzzing Adrian Herrera Hendra Gunadi Shane Magrath ANU & DST ANU DST Australia Australia Australia Michael Norrish Mathias Payer Antony L. Hosking CSIRO’s Data61 & ANU EPFL ANU & CSIRO’s Data61 Australia Switzerland Australia ABSTRACT ACM Reference Format: Mutation-based greybox fuzzing—unquestionably the most widely- Adrian Herrera, Hendra Gunadi, Shane Magrath, Michael Norrish, Mathias Payer, and Antony L. Hosking. 2021. Seed Selection for Successful Fuzzing. used fuzzing technique—relies on a set of non-crashing seed inputs In Proceedings of the 30th ACM SIGSOFT International Symposium on Software (a corpus) to bootstrap the bug-finding process. When evaluating a Testing and Analysis (ISSTA ’21), July 11–17, 2021, Virtual, Denmark. ACM, fuzzer, common approaches for constructing this corpus include: New York, NY, USA, 14 pages. https://doi.org/10.1145/3460319.3464795 (i) using an empty file; (ii) using a single seed representative of the target’s input format; or (iii) collecting a large number of seeds (e.g., 1 INTRODUCTION by crawling the Internet). Little thought is given to how this seed Fuzzing is a dynamic analysis technique for finding bugs and vul- choice affects the fuzzing process, and there is no consensus on nerabilities in software, triggering crashes in a target program by which approach is best (or even if a best approach exists). subjecting it to a large number of (possibly malformed) inputs. To address this gap in knowledge, we systematically investigate Mutation-based fuzzing typically uses an initial set of valid seed and evaluate how seed selection affects a fuzzer’s ability to find bugs inputs from which to generate new seeds by random mutation. -
A Novel Mricompatible Brain Ventricle Phantom for Validation of Segmentation and Volumetry Methods
CME JOURNAL OF MAGNETIC RESONANCE IMAGING 36:476–482 (2012) Original Research A Novel MRI-Compatible Brain Ventricle Phantom for Validation of Segmentation and Volumetry Methods Amanda F. Khan, MSc,1,2 John J. Drozd, PhD,2 Robert K. Moreland, MSc,2,3 Robert M. Ta, MSc,1,2 Michael J. Borrie, MB ChB,3,4 Robert Bartha, PhD1,2* and the Alzheimer’s Disease Neuroimaging Initiative Purpose: To create a standardized, MRI-compatible, life- Conclusion: The phantom represents a simple, realistic sized phantom of the brain ventricles to evaluate ventricle and objective method to test the accuracy of lateral ventri- segmentation methods using T1-weighted MRI. An objec- cle segmentation methods and we project it can be tive phantom is needed to test the many different segmen- extended to other anatomical structures. tation programs currently used to measure ventricle vol- Key Words: 3T; brain phantom; MRI; ventricle; software umes in patients with Alzheimer’s disease. validation; segmentation Materials and Methods: A ventricle model was con- J. Magn. Reson. Imaging 2012;36:476–482. structed from polycarbonate using a digital mesh of the VC 2012 Wiley Periodicals, Inc. ventricles created from the 3 Tesla (T) MRI of a subject with Alzheimer’s disease. The ventricle was placed in a brain mold and surrounded with material composed of VOLUMETRY HAS DEMONSTRATED that large mor- 2% agar in water, 0.01% NaCl and 0.0375 mM gadopente- phological changes occur in the brain during the tate dimeglumine to match the signal intensity properties course of Alzheimer’s disease (AD) (1). In particular, of brain tissue in 3T T -weighted MRI. -
Foot Prints Feel the Freedom of Fedora!
The Fedora Project: Foot Prints Feel The Freedom of Fedora! RRaahhuull SSuunnddaarraamm SSuunnddaarraamm@@ffeeddoorraapprroojjeecctt..oorrgg FFrreeee ((aass iinn ssppeeeecchh aanndd bbeeeerr)) AAddvviiccee 101011:: KKeeeepp iitt iinntteerraaccttiivvee!! Credit: Based on previous Fedora presentations from Red Hat and various community members. Using the age old wisdom and Indian, Free software tradition of standing on the shoulders of giants. Who the heck is Rahul? ( my favorite part of this presentation) ✔ Self elected Fedora project monkey and noisemaker ✔ Fedora Project Board Member ✔ Fedora Ambassadors steering committee member. ✔ Fedora Ambassador for India.. ✔ Editor for Fedora weekly reports. ✔ Fedora Websites, Documentation and Bug Triaging projects volunteer and miscellaneous few grunt work. Agenda ● Red Hat Linux to Fedora & RHEL - Why? ● What is Fedora ? ● What is the Fedora Project ? ● Who is behind the Fedora Project ? ● Primary Principles. ● What are the Fedora projects? ● Features, Future – Fedora Core 5 ... The beginning: Red Hat Linux 1994-2003 ● Released about every 6 months ● More stable “ .2” releases about every 18 months ● Rapid innovation ● Problems with retail channel sales model ● Impossible to support long-term ● Community Participation: ● Upstream Projects ● Beta Team / Bug Reporting The big split: Fedora and RHEL Red Hat had two separate, irreconcilable goals: ● To innovate rapidly. To provide stability for the long-term ● Red Hat Enterprise Linux (RHEL) ● Stable and supported for 7 years plus. A platform for 3rd party standardization ● Free as in speech ● Fedora Project / Fedora Core ● Rapid releases of Fedora Core, every 6 months ● Space to innovate. Fedora Core in the tradition of Red Hat Linux (“ FC1 == RHL10” ) Free as in speech, free as in beer, free as in community support ● Built and sponsored by Red Hat ● ...with increased community contributions. -
Medical Images Research Framework
Medical Images Research Framework Sabrina Musatian Alexander Lomakin Angelina Chizhova Saint Petersburg State University Saint Petersburg State University Saint Petersburg State University Saint Petersburg, Russia Saint Petersburg, Russia Saint Petersburg, Russia Email: [email protected] Email: [email protected] Email: [email protected] Abstract—with a growing interest in medical research problems for the development of medical instruments and to show and the introduction of machine learning methods for solving successful applications of this library on some real medical those, a need in an environment for integrating modern solu- cases. tions and algorithms into medical applications developed. The main goal of our research is to create medical images research 2. Existing systems for medical image process- framework (MIRF) as a solution for the above problem. MIRF ing is a free open–source platform for the development of medical tools with image processing. We created it to fill in the gap be- There are many open–source packages and software tween innovative research with medical images and integrating systems for working with medical images. Some of them are it into real–world patients treatments workflow. Within a short specifically dedicated for these purposes, others are adapted time, a developer can create a rich medical tool, using MIRF's to be used for medical procedures. modular architecture and a set of included features. MIRF Many of them comprise a set of instruments, dedicated takes the responsibility of handling common functionality for to solving typical tasks, such as images pre–processing medical images processing. The only thing required from the and analysis of the results – ITK [1], visualization – developer is integrating his functionality into a module and VTK [2], real–time pre–processing of images and video – choosing which of the other MIRF's features are needed in the OpenCV [3]. -
Is the Linux Desktop Less Secure Than Windows 10? Or How Super Mario Music Can Own Your System
IS THE LINUX DESKTOP LESS SECURE THAN WINDOWS 10? OR HOW SUPER MARIO MUSIC CAN OWN YOUR SYSTEM. Hanno Böck https://hboeck.de 1 This was too easy . It should not be possible to find a serious memory corruption vulnerability in the default Linux desktop attack surface with just a few minutes of looking. Although it’ s hard to say it, this is not the kind of situation that occurs with a latest Windows 10 default install. Is it possible that Linux desktop security has rotted? (Chris Evans) 2 NINTENDO SOUND FILES (1) Exploit against Gstreamer in Ubuntu 12.04 (LTS). Thumbnail parser. 3 NINTENDO SOUND FILES (2) NSF players are mini-emulators - the attacker can execute code in an emulator. Easier to bypass modern exploit mitigation techniques. 4 FIX The fix is to delete the affected NSF gstreamer plugin. No problem: Ubuntu shipped two different NSF player plugins. 5 FLIC EXPLOIT 6 AUTOMATIC DOWNLOADS Some browsers automatically download files to ~/Downloads. Any webpage can create files on your filesystem. (Chrome/Chromium, Epiphany, ... - not Linux specific) 7 TRACKER GNOME Desktop search tool automatically indexes all new files in a user's home - including ~/Downloads. 8 REACTION FROM TRACKER DEVELOPER Furthermore, the GStreamer guys were extremely fast in fixing it. You could claim that other libraries used for metadata extraction are just as insecure, but that'd really be bugs in these libraries to fix. (Carlos Garnacho) 9 TRACKER PARSERS (1) Gstreamer, ffmpeg, flac, totem-pl-parser, tiff, libvorbis, taglib, libpng, libexif, giflib, libjpeg-turbo, libosinfo, poppler, libxml2, exempi, libgxps, ghostscript, libitpcdata 10 TRACKER PARSERS (2) If you can exploit any of them you can exploit many Linux desktop users from the web without user interaction.