Noyau de système d'exploitation

Un noyau de système d’exploitation, ou simplement noyau, ou kernel en anglais, est une des parties fondamentales de certains systèmes d’exploitation. Il gère les ressources de l’ordinateur et permet aux différents composants — matériels et logiciels — de communiquer entre eux. En tant que partie du système d’exploitation, le noyau fournit des mécanismes d’abstraction du matériel, notamment de la mémoire, du (ou des) processeur(s), et des échanges d’informations entre logiciels et périphériques matériels. Le noyau autorise aussi diverses abstractions logicielles et facilite la communication entre les processus. Le noyau d’un système d’exploitation est lui-même un logiciel, mais ne peut cependant pas utiliser tous les mécanismes d’abstraction qu’il fournit aux autres logiciels. Son rôle central impose par ailleurs des performances élevées. Cela fait du noyau la partie la plus critique d’un système d’exploitation et rend sa conception et sa programmation particulièrement délicates. Pl

NrOS: Effective Replication and Sharing in an Operating System

Ankit Bhardwaj, Sanidhya Kashyap

Writing a correct operating system kernel is notoriously hard. Kernel code requires manual memory management and type-unsafe code and must efficiently handle complex, asynchronous events. In addition, increasing CPU core counts further complicate kernel development. Typically, monolithic kernels share state across cores and rely on one-off synchronization patterns that are specialized for each kernel structure or subsystem. Hence, kernel developers are constantly refining synchronization within OS kernels to improve scalability at the risk of introducing subtle bugs. We present NrOS, a new OS kernel with a safer approach to synchronization that runs many POSIX programs. NrOS is primarily constructed as a simple, sequential kernel with no concurrency, making it easier to develop and reason about its correctness. This kernel is scaled across NUMA nodes using node replication, a scheme inspired by state machine replication in distributed systems. NrOS replicates kernel state on each NUMA node and uses operation logs to maintain strong consistency between replicas. Cores can safely and concurrently read from their local kernel replica, eliminating remote NUMA accesses. Our evaluation shows that NrOS scales to 96 cores with performance that nearly always dominates Linux at scale, in some cases by orders of magnitude, while retaining much of the simplicity of a sequential kernel.

USENIX ASSOC2021

Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

Andy Roulin

Modern data-center network operating systems rely on proprietary user-space daemons wrapping SDKs from switch vendors. Linux-based variants of these operating systems have benefited from increasing and simplified dataplane offloading support in recent years: kernel resources such as routes and next hops are offloaded to hardware and the kernel can, e.g., learn new MAC entries seen from the hardware forwarding plane. However, the Linux kernel in these operating systems has to be extended and customized as it still lacks constructs (constructs exposed to user-space or in-kernel constructs) needed for complete control plane processing and dataplane offloading. Managing limited hardware resources and keeping the kernel and hardware forwarding planes equivalent are two examples of challenges where the lack of appropriate constructs forces switch operating systems to use user-space solutions coupled with proprietary SDKs and custom kernel modifications. Filling the gaps, i.e., designing and adding the missing constructs, would enable faster control plane processing (less user-kernel context switches) and faster dataplane configura- tion. It would also encourage in-tree kernel drivers from hardware vendors instead of the current closed-source user-space SDKs which would also improve performance while estab- lishing Linux as the standardized API for network switches. This thesis explores the different designs, performance challenges and trade-offs of completing the in-kernel switching API, starting from switch port configuration, faster control path packet processing and ending with in-kernel ASIC resource management. As most hardware vendors are not yet ready to open their drivers in the kernel, workarounds to still provide support for vendors’ SDKs through the same in-kernel API are presented as well. A user-space switch port driver for Mellanox switches was ported to kernel space in order to accelerate control plane processing and bootstrap the in-kernel switch port configuration design. A prefetching scheme which hides PCI latency was designed to manage limited and shared ASIC resources with synchronous feedback to user-space daemons in case of exhausted resources.

2018

Midas: Systematic Kernel TOCTTOU Protection

Atri Bhattacharyya, Mathias Josef Payer, Uros Tesic

Double-fetch bugs are a plague across all major operating system kernels. They occur when data is fetched twice across the user/kernel trust boundary while allowing concurrent modification. Such bugs enable an attacker to illegally access memory, cause denial of service, or to escalate privileges. So far, the only protection against double-fetch bugs is to detect and fix them. However, they remain incredibly hard to find. Similarly, they fundamentally prohibit efficient, kernel-based stateful system call filtering. We propose Midas to mitigate double-fetch bugs. Midas creates on-demand snapshots and copies of accessed data, enforcing our key invariant that throughout a syscall's lifetime, every read to a userspace object will return the same value. Midas shows no noticeable drop in performance when evaluated on compute-bound workloads. On system call heavy workloads, Midas incurs 0.2-14% performance overhead, while protecting the kernel against any TOCTTOU attacks. On average, Midas shows a 3.4% overhead on diverse workloads across two benchmark suites.

2022

Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

Andy Roulin

2018