A kernel in a library Genodes custom kernel approach Martin Stein - - PowerPoint PPT Presentation

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A kernel in a library Genodes custom kernel approach Martin Stein - - PowerPoint PPT Presentation

Mar 15, 2023 345 likes •800 views

A kernel in a library Genodes custom kernel approach Martin Stein < martin.stein@genode-labs.com > Outline 1. Motivation 2. Overview 3. Scheduling 4. Capabilities 5. Communication A kernel in a library Genodes custom kernel

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A kernel in a library Genode’s custom kernel approach

Martin Stein <martin.stein@genode-labs.com>

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Outline

  • 1. Motivation
  • 2. Overview
  • 3. Scheduling
  • 4. Capabilities
  • 5. Communication

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Outline

  • 1. Motivation
  • 2. Overview
  • 3. Scheduling
  • 4. Capabilities
  • 5. Communication

A kernel in a library Genode’s custom kernel approach 3

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Genode on third-party Kernels

The impetus of diversity NOVA, Fiasco.OC, OKL4, L4ka::Pistachio, L4/Fiasco, Linux SeL4

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Genode on third-party Kernels

The impetus of diversity NOVA, Fiasco.OC, OKL4, L4ka::Pistachio, L4/Fiasco, Linux SeL4 Flexibility in development and application

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Genode on third-party Kernels

The impetus of diversity NOVA, Fiasco.OC, OKL4, L4ka::Pistachio, L4/Fiasco, Linux SeL4 Flexibility in development and application Versatility in testing

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Genode on third-party Kernels

Kernel perspective Aim for comprehensive security concept

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Genode on third-party Kernels

Kernel perspective Aim for comprehensive security concept Self-contained unit that mistrusts all users

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Genode on third-party Kernels

Kernel perspective Aim for comprehensive security concept Self-contained unit that mistrusts all users Perspective of Genode’s Core Bring Kernel concept in line with Genode API

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Genode on third-party Kernels

Kernel perspective Aim for comprehensive security concept Self-contained unit that mistrusts all users Perspective of Genode’s Core Bring Kernel concept in line with Genode API Must be trusted anyway

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Genode on third-party Kernels

Drawbacks Concepts get bend in shape (Signals)

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Genode on third-party Kernels

Drawbacks Concepts get bend in shape (Signals) Work is done redundantly (memory management)

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Genode on third-party Kernels

Drawbacks Concepts get bend in shape (Signals) Work is done redundantly (memory management) Deficiencies get worked around (Capability delegation)

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Creating a custom solution

Idea Kernel that trusts Core and is designed for Core’s needs

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Creating a custom solution

Idea Kernel that trusts Core and is designed for Core’s needs Minimalistic library that enables Core to run as root domain

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Creating a custom solution

Idea Kernel that trusts Core and is designed for Core’s needs Minimalistic library that enables Core to run as root domain Run most critical code in the simplest manner

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Outline

  • 1. Motivation
  • 2. Overview
  • 3. Scheduling
  • 4. Capabilities
  • 5. Communication

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Kernel tasks

Exception vectors

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Kernel tasks

Exception vectors Scheduling

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Kernel tasks

Exception vectors Scheduling Controls interrupts

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Kernel tasks

Exception vectors Scheduling Controls interrupts Communication: IPC and Signals

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Kernel tasks

Exception vectors Scheduling Controls interrupts Communication: IPC and Signals Capabilities

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Kernel tasks

Exception vectors Scheduling Controls interrupts Communication: IPC and Signals Capabilities Cache and TLB maintenance

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Kernel tasks

Exception vectors Scheduling Controls interrupts Communication: IPC and Signals Capabilities Cache and TLB maintenance Virtualization

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Kernel interface

Threads, VMs PDs, Capabilities Communication, IRQs thread new/del

  • bj new/del

signal receiver new/del thread start pd new/del signal context new/del thread pause pd update irq new/del thread resume irq ack Core-only thread route event thread quota vm new/del vm run vm pause thread pause current update data region signal context kill thread resume local update instr region signal submit thread yield cap ack signal await Common cap delete signal ack msg send request msg send reply msg await request

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Qualities

All dynamic memory gets accounted → No exhaustion

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Qualities

All dynamic memory gets accounted → No exhaustion Modeled as state machine → Low complexity → Fast kernel passes

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Trusted Computing Base

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Trusted Computing Base

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Hardware support

ARMv7

◮ Panda Board, i.MX53 QSB, USB Armory, Wand Board,

Arndale, Odroid XU, Zynq, PBXA9

◮ SMP, Virtualization, Trustzone, ... A kernel in a library Genode’s custom kernel approach 14

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Hardware support

ARMv7

◮ Panda Board, i.MX53 QSB, USB Armory, Wand Board,

Arndale, Odroid XU, Zynq, PBXA9

◮ SMP, Virtualization, Trustzone, ...

x86 64 Bit, Raspberry Pi (ARMv6), RISC-V, Muen Separation Kernel

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Outline

  • 1. Motivation
  • 2. Overview
  • 3. Scheduling
  • 4. Capabilities
  • 5. Communication

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Scheduling

Absolute priorities

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Scheduling

Quota-bound priorities

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Scheduling

Quota-bound priorities

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Scheduling

Donation of CPU resources from parents to their children

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Outline

  • 1. Motivation
  • 2. Overview
  • 3. Scheduling
  • 4. Capabilities
  • 5. Communication

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Capabilities

Automatic creation or translation on IPC delegation

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Capabilities

Automatic creation or translation on IPC delegation No name diversity in a PD

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Capabilities

Automatic creation or translation on IPC delegation No name diversity in a PD Costs get accounted via PD session quota

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Capabilities

Collaborative lifetime management for Capabilities

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Outline

  • 1. Motivation
  • 2. Overview
  • 3. Scheduling
  • 4. Capabilities
  • 5. Communication

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Communication

IPC implicitely delegates CPU resources

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Communication

Collaborative lifetime management for Signals

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Thank you!

Genode OS Framework http://genode.org Genode Labs GmbH http://genode-labs.com Source code at GitHub http://github.com/genodelabs/genode

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