Kernel Source Tree

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The Experts below are selected from a list of 54 Experts worldwide ranked by ideXlab platform

E A Cherkashin - One of the best experts on this subject based on the ideXlab platform.

A Y Sokolov - One of the best experts on this subject based on the ideXlab platform.

Emmett Witchel - One of the best experts on this subject based on the ideXlab platform.

  • GPUfs: Integrating a file system with GPUs
    ACM Transactions on Computer Systems, 2014
    Co-Authors: Mark Silberstein, Bryan Ford, Idit Keidar, Emmett Witchel
    Abstract:

    As GPU hardware becomes increasingly general-purpose, it is quickly outgrowing the traditional, constrained GPU-as-coprocessor programming model. This article advocates for extending standard operating system services and abstractions to GPUs in order to facilitate program development and enable harmonious integration of GPUs in computing systems. As an example, we describe the design and implementation of GPUFs, a software layer which provides operating system support for accessing host files directly from GPU programs. GPUFs provides a POSIX-like API, exploits GPU parallelism for efficiency, and optimizes GPU file access by extending the host CPU's buffer cache into GPU memory. Our experiments, based on a set of real benchmarks adapted to use our file system, demonstrate the feasibility and benefits of the GPUFs approach. For example, a self-contained GPU program that searches for a set of strings throughout the Linux Kernel Source Tree runs over seven times faster than on an eight-core CPU.

  • GPUfs: Integrating a File System with GPUs
    2013
    Co-Authors: Mark Silberstein, Bryan Ford, Idit Keidar, Emmett Witchel
    Abstract:

    As GPU hardware becomes increasingly general-purpose, it is quickly outgrowing the traditional, constrained GPU-as-coprocessor programming model. To make GPUs easier to program and improve their integration with operating systems, we propose making the host’s file system directly accessible to GPU code. GPUfs provides a POSIX-like API for GPU programs, exploits GPU parallelism for efficiency, and optimizes GPU file access by extending the host CPU’s buffer cache into GPU memory. Our experiments, based on a set of real benchmarks adapted to use our file system, demonstrate the feasibility and benefits of the GPUfs approach. For example, a self-contained GPU program that searches for a set of strings throughout the Linux Kernel Source Tree runs over seven times faster than on an eight-core CPU

Gilles Muller - One of the best experts on this subject based on the ideXlab platform.

  • Fork/Wait and Multicore Frequency Scaling: a Generational Clash
    2019
    Co-Authors: Damien Carver, Julia Lawall, Nicolas Palix, Redha Gouicem, Jean-pierre Lozi, Julien Sopena, Baptiste Lepers, Willy Zwaenepoel, Gilles Muller
    Abstract:

    The complexity of computer architectures has risen since the early years of the Linux Kernel: Simultaneous Multi-Threading (SMT), multicore processing, and frequency scaling with complex algorithms such as Intel ® Turbo Boost have all become omnipresent. In order to keep up with hardware innovations, the Linux scheduler has been rewritten several times, and many hardware-related heuristics have been added. Despite this, we show in this paper that a fundamental problem was never identified: the POSIX process creation model, i.e., fork/wait, can behave inefficiently on current multicore architectures due to frequency scaling. We investigate this issue through a simple case study: the compilation of the Linux Kernel Source Tree. To do this, we develop SchedLog, a low-overhead scheduler tracing tool, and SchedDisplay, a scriptable tool to graphically analyze SchedLog's traces efficiently. We implement two solutions to the problem at the sched-uler level which improve the speed of compiling part of the Linux Kernel by up to 26%, and the whole Kernel by up to 10%.

  • Enforcing the use of API functions in linux code
    Proceedings of the 8th workshop on Aspects components and patterns for infrastructure software - ACP4IS '09, 2009
    Co-Authors: Julia Lawall, Gilles Muller, Nicolas Palix
    Abstract:

    In the Linux Kernel Source Tree, header files typically define many small functions that have a simple behavior but are critical to ensure readability, correctness, and maintainability. We have observed, however, that some Linux code does not use these functions systematically. In this paper, we propose an approach combining rule-based program matching and transformation with generative programming to generate rules for finding and fixing code fragments that should use the functions defined in header files. We illustrate our approach using an in-depth study based on four typical functions defined in the header file include/linux/usb.h.

  • PLOS - Semantic patches for documenting and automating collateral evolutions in Linux device drivers
    Proceedings of the 3rd workshop on Programming languages and operating systems linguistic support for modern operating systems - PLOS '06, 2006
    Co-Authors: Yoann Padioleau, Julia Lawall, René Rydhof Hansen, Gilles Muller
    Abstract:

    Developing and maintaining drivers is known to be one of the major challenges in creating a general-purpose, practically-useful operating system [1, 3]. In the case of Linux, device drivers make up, by far, the largest part of the Kernel Source code, and many more drivers are available outside the standard Kernel Source Tree. New drivers are needed all the time, to give access to the latest devices. To ease driver development, Linux provides a set of driver support libraries, each devoted to a particular bus or device type. These libraries encapsulate much of the complexity of interacting with the device and the Linux Kernel, and impose a uniform structure on device-specific code within a given bus or device type.

I R Golovko - One of the best experts on this subject based on the ideXlab platform.