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Symbiotic Virtualization John R. Lange Ph.D. Final Defense Department of Electrical Engineering and Computer Science Northwestern University August 9,

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Presentation on theme: "Symbiotic Virtualization John R. Lange Ph.D. Final Defense Department of Electrical Engineering and Computer Science Northwestern University August 9,"— Presentation transcript:

1 Symbiotic Virtualization John R. Lange Ph.D. Final Defense Department of Electrical Engineering and Computer Science Northwestern University August 9, 2010

2 2 Thesis Current VMM architectures use lowlevel interfaces –Do not expose high level semantic information VMMs have little knowledge of internal guest behavior –Large semantic gap Symbiotic Virtualization –New approach for designing virtual architectures –Exposes high level semantic information Bidirectional synchronous and asynchronous communication

3 3 Outline Palacios –Developed first VMM for scalable High Performance Computing (HPC) Largest scale study of virtualization –Proved HPC virtualization is effective at scale Symbiotic Virtualization (SymSpy) –High level interfaces to enable guest/VMM cooperation SymCall and SwapBypass –Leverage symbiotic interfaces to improve swap performance SymMod –Extend guest OS with arbitrary interfaces/functionality

4 4 Past and Current Research Palacios: Symbiotic virtualization at scale –In progress: Scalable virtualization for HPC –In progress: Symbiotic Virtualization –IPDPS 2010: Palacios VMM and scaling –In progress: Adaptive virtual paging –WIOV 2008: Virtual passthrough I/O –OSR 2009: Virtual passthrough I/O Empathic Systems: Bridging systems and HCI –INFOCOM 2010: Empathic networks –SIGMETRICS 2009: Empathic networks –USENIX 2008: Speculative remote display Virtuoso: Adaptive virtual infrastructure as a service (IaaS) cloud –HPDC 2007: Transparent network services –ICAC 2006: Formalization of cloud adaptation –MAMA 2005: Formalization of cloud adaptation –HPDC 2005: Automatic optical network reservations –Patent # 20080155537 Vortex: Cooperative traffic aggregation for intrusion detection systems –RAID 2007: Cooperative selective wormholes

5 5 What are VMMs currently used for? Enterprise and Data centers –Server Consolidation –Fault tolerance –Legacy application support –Debugging –Isolation –Virtual appliances –Failover and disaster recovery None specifically designed for other areas –HPC, education, architecture research $16.70 Billion $7.58 Billion

6 6 Virtualization in HPC Fault tolerance –RedStorm MTBI target: 50 hours –RedStorm Min TTR: 30 minutes – 1 hour Broader usage –Allow applications to select best OS Only if it doesn’t degrade performance… –Tightly coupled parallel applications –Very large scale A.B. Nagarajan, F. Mueller, C. Engelmann, and S.L. Scott Proactive Fault Tolerance for HPC with Xen Virtualization ICS 2007

7 7 Scalability Scale causes lots of problems –Small intra-node performance losses become incredibly large Per-node overhead has a Butterfly Effect –OS timers, deferred work, kernel threads –“OS Noise” Linux reduces performance by X% Linux delivers performance of ~0% Performance at scale is not always correlated with local performance –5% loss for 1 node does not equal 5% loss at scale –Example: Paragon

8 8 Kitten Open-source Lightweight Kernel –Exports Linux compatible ABI Subset of features LWK for a wide range of HPC applications –Open source version of Catamount lineage Contributing developer –http://software.sandia.gov/trac/kitten –http://code.google.com/p/kitten/

9 9 Palacios VMM OS-independent embeddable virtual machine monitor Developed at Northwestern and University of New Mexico –Lead developer and graduate student Open source and freely available –Downloaded over 1000 times as of July Users: –Kitten: Lightweight supercomputing OS from Sandia National Labs –MINIX 3 –Modified Linux versions Successfully used on supercomputers, clusters (Infiniband and Ethernet), and servers http://www.v3vee.org/palacios

10 10 People Myself: Lead architect and developer Peter Dinda and Patrick Bridges –Project PIs Lei Xia, Chang Bae, Zheng Cui, Phil Soltero, and Yuan Tang –Graduate students Andy Gocke, Steven Jaconette, Rob Deloatch, Rumou Duan, Jason Lee, Madhav Suresh, Brad Weinberger, Matt Wojcik, and Peter Kamm –Undergraduate students Kevin Pedretti and Trammell Hudson –Collaborators at Sandia National Labs Many others

11 11 Palacios as an HPC VMM Minimalist interface –Suitable for an LWK Compile and runtime configurability –Create a VMM tailored to specific environments Low noise Contiguous memory pre-allocation Passthrough resources and resource partitioning

12 12 HPC Performance Evaluation Virtualization is very useful for HPC, but… Only if it doesn’t hurt performance Virtualized RedStorm with Palacios –Evaluated with Sandia’s system evaluation benchmarks 17 th fastest supercomputer Cray XT3 38208 cores ~3500 sq ft 2.5 MegaWatts $90 million

13 13 Scalability at Small Scales (Catamount) Within 5% Scalable HPCCG: conjugant gradient solver

14 14 CatamountCompute Node Linux Comparison of Operating Systems HPCCG: conjugant gradient solver Shadow Paging

15 15 Large Scale Study Evaluation on full RedStorm system –12 hours of dedicated system time on full machine –Largest virtualization performance scaling study to date Measured performance at exponentially increasing scales –Up to 4096 nodes Publicity –New York Times –Slashdot –HPCWire –Communications of the ACM –PC World

16 16 Scalability at Large Scale (Catamount) CTH: multi-material, large deformation, strong shockwave simulation Within 3% Scalable

17 17 Summary Virtualization can scale –Near native performance for optimized VMM/guest (within 5%) VMM needs to know about guest internals –Should modify behavior for each guest environment –Example: Paging method to use depends on guest Black Box inference is not desirable in HPC environment –Unacceptable performance overhead –Convergence time –Mistakes have large consequences Need guest cooperation –Guest and VMM relationship should be symbiotic (Thesis)

18 18 Semantic Gap VMM architectures are designed as black boxes –Explicit lowlevel OS interface (hardware or paravirtual) –Internal OS state is not exposed to the VMM Many uses for internal state –Performance, security, etc... –VMM must recreate that state “Bridging the Semantic Gap” –[Chen: HotOS 2001] Two existing approaches: Black Box and Gray Box –Black Box: Monitor external guest interactions –Gray Box: Reverse engineer internal guest state –Examples Virtuoso Project (Early graduate work) Lycosid, Antfarm, Geiger, IBMon, many others

19 19 Example: Swapping Physical Memory Swapped Memory Application Memory Working Set Swap Disk Disk storage for expanding physical memory Only basic knowledge without internal state Guest VMM

20 20 Symbiotic Virtualization Bridging the semantic gap is hard –Can we design a virtual machine interface with no gap? Symbiotic Virtualization –Design both guest OS and VMM to minimize semantic gap –Bidirectional synchronous and asynchronous communication channels –Interfaces are optional Non-symbiotic OS can run on symbiotic VMM Symbiotic OS can run on real hardware

21 21 Symbiotic Interfaces SymSpy Passive Interface –Internal state already exists but it is hidden –Asynchronous bi-directional communication via shared memory –Structured state information that is easily parsed Semantically rich SymCall Functional Interface –Synchronous upcalls into guest during exit handling –API Function call in VMM System call in Guest –Brand new interface construct

22 22 Discovery and Configuration A symbiotic OS must run on real hardware –Interface must be based on hardware features CPUID –Detection of Symbiotic VMM MSRs –Configuration of Symbiotic interfaces

23 23 SymSpy Shared memory page between OS and VMM –Global and per-core interfaces Standardized data structures –Shared state information Read and write without exits

24 24 PCI passthrough (with SymSpy) 2 node Infiniband Ping Pong bandwidth measurement (Linux guest on Infiniband cluster)

25 25 SymCall (Symbiotic Upcalls) Conceptually similar to System Calls –System Calls: Application requests OS services –Symbiotic Upcalls: VMM requests OS services Designed to be architecturally similar –Virtual hardware interface Superset of System Call MSRs –Internal OS implementation Share same system call data structures and basic operations Guest OS configures a special execution context –VMM instantiates that context to execute synchronous upcall –Symcalls exit via a dedicated hypercall

26 26 SymCall Control Flow Handle exit Running in guest Return to VMM Nested Exits

27 27 Implementation Symbiotic Linux guest OS –Exports SymSpy and SymCall interfaces Palacios –Fairly significant modifications to enable nested VM entries Re-entrant exit handlers Serialize subset of guest state out of global hardware structures

28 28 SwapBypass Purpose: improve performance when swapping –Temporarily expand guest memory –Completely bypass the Linux swap subsystem Enabled by SymCall –Not feasible without symbiotic interfaces VMM detects guest thrashing –Shadow page tables used to prevent it

29 29 Symbiotic Shadow Page tables Guest Page TablesShadow Page Tables Page Directory Page Table Physical Memory Page Directory Page Table Physical Memory Swap Disk Cache Swapped out pageSwap Bypass Page

30 30 Guest 3 Global Swap Disk Cache Guest 1 SwapBypass Concept Guest Physical Memory Swapped Memory Swap Disk Application Working Set VMM physical Memory Swap Disk Guest 2 Guest 3

31 31 Necessary SymCall: query_vaddr() 1.Get current process ID –get_current(); (Internal Linux API) 2.Determine presence in Linux swap cache –find_get_page(); (Internal Linux API) 3.Determine page permissions for virtual address –find_vma(); (Internal Linux API) Information extremely hard to get otherwise Must be collected while exit is being handled

32 32 Evaluation Memory system micro-benchmarks –Stream, GUPS, ECT Memperf –Configured to over commit anonymous memory Cause thrashing in the guest OS Overhead isolated to swap subsystem –Ideal swap device implemented as RAM disk I/O occurs at main memory speeds Provides lower bound for performance gains

33 33 Bypassing Swap Overhead Working set size Ideal I/O improvement Stream: simple vector kernel Performance improves

34 34 SymMod (Symbiotic Modules) SymSpy/SymCall: explicit interfaces –Guest OS must support each specific one With migration, VMs not tied to hardware –Virtual environment (hardware and devices) can change –Currently, OSes must include all possible device drivers Guest OS might lack functionality SymMod: Extend guest OS with arbitrary interfaces/functionality –VMM loads code directly into guest –Implementation in Palacios and Linux OS drivers Standard Symbiotic Modules Secure Symbiotic Modules

35 35 Access standard OS driver API –Dependent on internal OS implementation OS Drivers/Modules

36 36 Standard Symbiotic Modules Guest exposes standard symbiotic API via SymSpy

37 37 Secure Symbiotic Modules Symbiotic API, protected from guest –Secure initialization –Virtual memory overlay

38 38 Summary and Contributions Designed and implemented the Palacios VMM –OS independent embeddable VMM Virtualization can scale –Near native performance for optimized VMM/guest (within 5%) VMM needs to know about guest internals –Bridge the semantic gap –Black Box inference is not desirable in HPC environment Need guest cooperation –Guest and VMM relationship should be symbiotic Symbiotic Virtualization –SymSpy and SymCall interfaces –SymMod extensions


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