PPT - Duke Computer Science
Download
Report
Transcript PPT - Duke Computer Science
CPS110:
Wrapping up memory
Landon Cox
March 6, 2008
Traditional OS structure
App
App
App
Operating System
Host Machine
App
OS abstractions
Threads
Instructions
CPU
Last month of class
Applications
Virtual
Memory
OS
Virtual addrs
Physical mem
Hardware
What are the interfaces and the resources?
What is being virtualized?
“Kernel
library”
Syst calls
I/O devices
Courser abstraction: virtual machine
We’ve already seen a kind of virtual machine
OS gives processes virtual memory
Each process runs on a virtualized CPU
Virtual machine
An execution environment
May or may not correspond to physical reality
Virtual machine options
How to implement a virtual machine?
1. Interpreted virtual machines
Translate every VM instruction
Kind of like on-the-fly compilation
VM instruction HW instruction(s)
2.
Direct execution
Execute instructions directly
Emulate the hard ones
Interpreted virtual machines
Implement the machine in software
Must translate emulated to physical
Java: byte codes x86, PPC, ARM, etc
Software fetches/executes instructions
Program
(foo.class)
Byte code
Interpreter
(java)
x86
What does this picture look like?
Dynamic virtual memory translator
Java virtual machine
What is the interface?
Java byte-code instructions
What is the abstraction?
Stack-machine architecture
What are the resources?
CPU, physical memory, disk, network
The Java programming language
High-level language compiled into byte code
Library of services (kind of like a kernel)
Like C++/STL, C#
Direct execution
What is the interface?
Hardware ISA (e.g. x86 instructions)
What is the abstraction?
Physical machine (e.g. x86 processor)
What are the resources?
CPU, physical memory, disk, network
Program
(XP kernel)
x86
Monitor
(VMware)
Different techniques
Emulation
Bochs, QEMU
Full virtualization
VMware
Paravirtualization
Xen
Dynamic recompilation
Virtual PC
Virtual machines are hot
VMware IPO: $19.1 billion
Xen sale: $500 million
Views of the CPU
How is a process’s view of the CPU different than the OS’s?
Kernel mode
Access to physical memory
Manipulation of page tables
Other “privileged instructions”
Turn off interrupts
Traps
Keep these in mind when thinking about virtual machines
Virtual machine structure
Guest
App
Guest
App
Guest
App
Guest OS
Guest OS
Guest OS
Virtual Machine Monitor (Hypervisor)
Host Machine
Why are hypervisors useful?
Code reuse
Can run old operating systems + apps on new hardware
Original purpose of VMs by IBM in the 60s
Encapsulation
Can put entire state of an “application” in one thing
Move it, restore it, copy it, etc
Isolation, security
All interactions with hardware are mediated
Hypervisor can keep one VM from affecting another
Hypervisor cannot be corrupted by guest operating systems
Encapsulation
Say I want to suspend/restore an application
I decide to write the process mem + PCB to disk
I reboot my kernel and restart the process
Will this work?
No, application state is spread out in many places
Application might involve multiple processes
Applications have state in the kernel (lost on reboot)
(e.g. open files, locks, process ids, driver states, etc)
Encapsulation
Virtual machines capture all of this state
Can suspend/restore an application
On same machine between boots
On different machines
Very useful in server farms
We’ll talk more about this with Xen
Security
Can user processes corrupt the kernel?
Can overwrite logs
Overwrite kernel file
Can boot a new kernel
Exploit a bug in the system call interface
Ok, so I’ll use a hypervisor. Is my data any less vulnerable?
All the state in the guest is still vulnerable (file systems, etc)
So what’s the point?
Hypervisors can observe the guest OS
Security services in hypervisor are safe, makes detection easier
Security
Hypervisors buggy too, why trust them more than kernels?
Narrower interface to malicious code (no system calls)
No way for kernel to call into hypervisor
Smaller, (hopefully) less complex codebase
Should be fewer bugs
Anything wrong with this argument?
Hypervisors are still complex
May be able to take over hypervisor via non-syscall interfaces
E.g. what if hypervisor is running IP-accessible services?
Paravirtualization (in Xen) may compromise this
VMware architecture
Host World
VMM World
Target
App
Host
App
VM App
Host OSVM Driver
Host Machine
Target
App
Target OS
Virtual Machine
Monitor
SimOS (proto-VMware) arch.
Target
App
Target
App
Target OS
Host
App
SimOS
Host OS
Host Machine
Host
App
SimOS memory
SimOS
SimOS VMemory
SimOS code, data
Target OS
TargOS code, data
Target App
TargApp code, data
Target App
Virtual MMU
SimDisk
Host OS
Host Machine
SimDisk File
Mem File
SimOS page fault
SimOS
SimOS VMemory
Target OS
Target App
Target App
SimOS Fault handler
What if I want to
TargOS Fault handler
suspend and
Unmapped
addr
migrate
the target
OS?
Virtual MMU
SimDisk
Host OS
Host Machine
SimDisk File
Mem File
Full vs interpreted
Why would I use VMware instead of Java?
Support for legacy applications
Do not force users to use a particular language
Do not force users to use a particular OS
Why would I use Java instead of VMware?
Lighter weight
Nice properties of type-safe language
Can prove safety at compile time
Full vs interpreted
What about protection?
What does Java use for protection? VMware?
Java relies on language features (cannot express unsafe computation)
VMware relies on the hardware to enforce protection (like an OS)
What are the trade-offs? Which protection model is better?
Java gives you stronger (i.e. provable) safety guarantees
Hardware protection doesn’t constrain programming expressiveness
What about sharing (kind of the opposite of protection)?
Sharing among components in Java is easy
(call a function, compiler makes sure it is safe)
Sharing between address spaces is more work, has higher overhead
(use sockets, have to context switch, flush TLB, etc)
Singularity (could try both)
Virtual machine challenges
Privilege modes
Memory management
Protection
Performance
Many more for every architecture…
Course administration
Multi-process test cases
Autograder will test your pager with > 1 process
But don’t submit any to the autograder
How to write multi-process test cases
Use vm_yield
Can quickly open processes in different windows
Can use sleep (unsigned int seconds)
Could use fork
Course administration
Extra office hours after spring break
Will announce over Blackboard
Other questions?
Sharing machines among users
PlanetLab (752 nodes at 361 sites)
Platform for distributed applications
Research testbed
Why is this more useful than a cluster?
See real Internet problems
Latency, failures, etc
Service fault tolerance
Sharing machines among users
Consolidate under-utilized servers
to reduce CapEx and OpEx
Avoid downtime with relocation
Dynamically re-balance workload
to guarantee application SLAs
Enforce security policy
What about the enterprise?
Sharing machines among users
When?
PlanetLab (testbeds, distributed services)
Data centers (three-tier web applications)
Scientific computing (protein folding, etc)
What should the interface be?
Shared infrastructure interfaces
Unmodified OS
Each app gets a login username
Access resources through system calls
Users can see other users’ files, processes
Drawbacks of this approach?
Administration, configuration headaches
(e.g. which libraries are installed?)
No performance isolation
(one process can dominate CPU, buffer cache, bandwidth)
Shared infrastructure interfaces
Unmodified OS
Retrofit resource accounting into OS (V-Servers)
Access resources through system calls
Virtualize some resources
(e.g. each app has own process table, file system)
Drawbacks of this approach?
How do you know that you’ve virtualized everything you need to
Especially hard for software resources
(e.g. what about entries in the file descriptor table?)
(e.g. who gets charged on a page fault?)
Shared infrastructure interfaces
Unmodified OS
Retrofit resource accounting into OS (V-Servers)
Virtual machines (Xen, VMware)
Virtualize hardware interface
Each app gets to choose its own OS
(e.g. apps have their own virt. CPU, physical memory, disk)
Drawbacks of this approach?
Very heavy-weight
A lot of redundant state (e.g. kernel, libraries, executables)
Might not scale well
Amazon EC2
Anyone know what EC2 uses?
Xen
Xen challenges
Kind of the opposite approach of V-Servers
V-Servers: start with OS, virtualize
Xen: start with VM, “para-virtualize”
Goals
Performance isolation
Support many operating systems
Reduce performance overhead of virtualization
Para-virtualization
Full virtualization
Fool OS into thinking it has access to hardware
Para-virtualization
Expose real and virtual resources to OS
Why do we need para-virtualization?
Mostly because X86 makes full virtualization hard
Why para-virtualize?
Limitations of x86
Privileged instructions fail silently
VMM must execute these instructions
Cannot rely on traps to VMM
How does VMware deal with this?
At run-time rewrite guest kernel binary
Insert traps into the VMM, when necessary
Why para-virtualize?
Limitations of x86
Timing issues
May want to expose “real time” to OS
TCP time outs, RTT estimates
Support for performance optimizations
Superpages
Page coloring
VMware architecture
Host World
VMM World
Target
App
Host
App
VM App
Host OSVM Driver
Host Machine
Target
App
Target OS
Virtual Machine
Monitor
SimOS architecture
Target
App
Target
App
Target OS
Host
App
SimOS
Host OS
Host Machine
Host
App
Xen architecture
Guest
App
Guest
App
Guest OS
Guest OS
Host
App
Xen
Domain 0
Host Machine
X86_32 address space
When are each set of virtual addresses are valid?
4GB
3GB
Xen
S
Kernel
S
User
All
address
spaces
All of a
VM’s
address
spaces
U
0GB
When does the hypervisor need to flush the TLB?
When a new guest VM or guest app needs to be run.
Each
guest
app
Xen physical memory
Allocated by hypervisor when VM is created
Why can’t we allow guests to update PTBR?
Might map virtual addrs to physical addrs they don’t own
VMware and Xen handled this differently
VMware maintains “shadow page tables”
Xen uses “hypercalls”
(update: Xen and VMware support both mechanisms now)
VMware guest page tables
Virtual → Machine
Update PTE
Guest OS
How does VMM grab control when PTE is updated?
Marks PTE pages read-only, generates page fault.
Shadow page table
VMM
Hardware
MMU
Xen physical memory
Guest OSes allocate and manage own PTs
“Hypercall” to change PT base
Like a system call between guest OS and Xen
Xen must validate PT updates before use
What are the validation rules?
1. Guest may only map phys. pages it owns
2. PT pages may only be mapped RO
Xen guest page tables
Virtual → Machine
Update PTE hypercall
Guest OS
1) Validation check
2) Perform update
VMM
Hardware
MMU
Para-virtualized CPU
Hypervisor runs at higher privilege than guest OS
Why is having only two levels a problem?
Guest OSes must be protected from guest applications
Hypervisor must be protected from guest OS
What do we do if we only have two privilege levels?
OS shares lower privilege level with guest applications
Run guest apps and guest OS in different address spaces
Why would this be slow?
VMM must flush the TLB on system calls, page faults
X86_32 address space
4GB
3GB
Xen
Kernel
S
S
Ring 0
Ring 1
Ring 3
User
U
0GB
What does this assume?
Guest OS doesn’t need ring 2 (e.g. OS/2).
Para-virtualized CPU
Hypervisor runs at higher privilege than guest OS
Ring 0 hypervisor, ring 1 guest OS, ring 3 guest apps
Handling exceptions
Guest registers handlers with Xen (must modify guest)
System calls
Guests register "fast" handler with Xen
Xen validates handler, inserts in CPU’s handler table
No need to go to ring 0 to execute
What handler cannot be executed directly and why?
Page fault handler must read register CR2 (only allowed in ring 0)
CR2 is where the fault-generating address is stored
Para-virtualization
Pros
Better performance
Scales better than full virtualization
Cons
OS needs (minor) changes
How well does it actually scale? Unclear at this point
Impure abstractions
Is it important to provide good abstractions?
I say yes
Bad interfaces lead to code complexity, maintainability issues