Operating System Organization the topic is overall o/s design lots of ways to structure an o/s -- how to decide? looking for principles and approaches what does an o/s *have* to do? for e.g. desktop or server use let apps use machine resources multiplex resources among apps isolate / protect allow cooperation / interaction we'll talk about three approaches, but others exist e.g. Java VM what's the traditional approach? (Linux, xv6) virtualize some resources: cpu and memory simulate a dedicated cpu and memory system for each app why? it's a simple model for app programmers abstract others: storage, network, IPC layer a sharable abstraction over h/w (file system, IP/TCP) example: virtualize the cpu (show slide on processes = simplicity) goal: simulate a dedicated cpu for each process we want transparent CPU multiplexing process need not think about how it interacts w/ other processes o/s runs different processes in turn, via clock interrupt clock means process doesn't need to do anything special to switch also prevents hogging how to achieve transparency? o/s saves state, then restores what does o/s save? eight regs, EIP, seg regs, eflags, page table base ptr where does o/s save it? o/s keeps per-process table of saved states the return from clock interrupt restores a *different* process's state the point: process doesn't have to worry about multiplexing! note: while this is the traditioal approach to virtualizing the CPU, maybe not the best: see exokernel paper type 'ps' on shell. How does 'ps' work? example: virtualize memory (show slide on processes = isolation) idea: simulate a complete memory system for each process so process has complete freedom how it uses that memory doesn't have to worry about other processes so addresses 0..2^32 all work, but refer to private memory convenient: all programs can start at zero and memory looks contiguous, good for large arrays &c safe: can't even *name* another process's memory again: traditional but we'll soon see it's a very limiting approach really want apps to have more control than this style of VM implies how can we do this? after all, the processes do in fact share the RAM how to create address spaces? (show figure) could have only one process at a time in physical memory would spend lots of time swapping in and out to disk made sense 40 years ago w/ small memory machines could use x86 segments (show figure) put each process in a different range of physical memory CS, DS, &c point to current process's base looks good: addresses start at zero, contiguous, isolation this is how x86 and original unix worked need to prevent process from modifying seg regs but allow kernel to modify them 386 has the hardware we need h/w "privilege level" bit: on in kernel, off in apps and ways to jump back and forth (syscalls, interrupts, return) but: fragmentation (show figure), all mem must be resident, can't have vm > phys could use x86 paging hardware MMU array w/ entry for each 4k range of "virtual" address space refers to phy address for that "page" this is the page table now we don't have a fragmentation problem o/s tells h/w to switch page table when switching process level of indirection allows o/s to play other tricks demand paging: (explain using figure) process bigger than available physical memory? "page-out" (write) pages to disk, mark PTEs invalid if process tries to use one of those pages, MMU causes page fault kern finds phys mem, page-in from disk, mark PTE valid this works because apps use only a fraction of mem at a given time need h/w valid flag, page faults, and re-startable instructions copy-on-write: avoid copy implied by fork() -- won't be needed if exec() make parent and child share the physical memory pages if either writes, do the copy then so need per-page write-protect flag both of above are transparent to application still thinks it has simple dedicated memory from 0..2^32 paging h/w has turned out to be one of the most fruitful ideas in o/s you'll be using it a lot in labs. The "right" page size is an engineering decision. What should it depend on? Guesses on the approximate page size? Process = Thread + Address Space In theory, each process (or thread) is an independent turing machine (show slide on 'the multithreading illusion') Threads versus Procedures Threads may resume out of order - cannot use LIFO stack to save state - general solution: duplicate stack Threads switch less often - Don't partition registers (why?) Threads involuntarily interrupted - Thread switch code saves all registers (compare with procedure call) More than one thread can run - Scheduling (who to run next?) becomes an issue - For procedures, the candidate to run is obvious Process != Program (show slide) o/s = event-driven while (1) { wait for an event; respond to the event; } event examples: - user program issues a system call to read a file - disk controller finishes reading the disk block and generates interrupt - A firefox user asks for a URL to be retrieved - Packet arrives over network - Timer interrupt fires o/s organization step back, what does a traditional o/s look like? traditional organization: monolithic o/s h/w, kernel, user kernel is a big program: process ctl, vm, fs, network all of kernel runs w/ full hardware privilege (very convenient) good: easy for sub-systems to cooperate (e.g. paging and file system) bad: interactions => complex, bugs are easy, no isolation within o/s philosophy: convenience (for app or o/s programmer) for any problem, either hide it from app, or add a new system call (we need philosophy because there is not much science here) very successful approach alterate organization: microkernel philosophy: IPC and user-space servers for any problem, make a new server, talk to it w/ RPC h/w, kernel, server processes, apps servers: VM, FS, TCP/IP, Print, Display split up kernel sub-systems into server processes some servers have privileged access to some h/w (e.g. FS and disks) apps talk to them via IPC / RPC kernel's main job: fast IPC good: simple/efficient kernel, sub-systems isolated, enforced better modularity bad: cross-sub-system optimization harder, lots of IPCs may be slow in the end, lots of good individual ideas, but overall plan didn't catch on alternate organization: exokernel philosophy: eliminate all abstractions for any problem, expose h/w or info to app, let app do what it wants h/w, kernel, environments, libOS, app an exokernel would not provide address space, virtual cpu, file system, TCP instead, give control to app: phys pages, addr mappings, clock interrupts, disk i/o, net i/o let app build nice address space if it wants, or not should give aggressive apps much more flexibility challenges: how to multiplex cpu/mem/&c if you expose directly to apps? how to get security/isolation despite apps having low-level control? how to multiplex w/o understanding: disk (file system), incoming tcp pkts exokernel example: memory what are the resources? (phys pages, mappings) what does an app need to ask the kernel to do? pa = AllocPage() DeallocPage(pa) TLBwr(va, pa) and these kernel->app upcalls: PageFault(va) PleaseReleaseAPage() what does o/s need to do to make multiplexing work? ensure app only creates mappings to phys pages it owns track what env owns what phys pages decide which app to ask to give up a phys page when system runs out that app gets to decide which of its pages simple example: shared memory two processes want to share memory, for fast interaction note traditional "virtual address space" doesn't allow for this process a: pa = AllocPage() put 0x5000 -> pa in private table PageFault(0x5000) upcall -> TLBwr(0x5000, pa) give pa to process b (need to tell exokernel...) process b: put 0x6000 -> pa in private table ... example cool thing you could do w/ exokernel-style memory databases like to keep a cache of disk pages in memory problem on traditional o/s: assume an o/s with demand-paging to/from disk if DB caches some disk data, and o/s needs a phys page, o/s may page-out a DB page holding a cached disk block but that's a waste of time: if DB knew, it could release phys page w/o writing, and later read it back from DB file (not paging area) 1. exokernel needs phys mem for some other app 2. exokernel sends DB a PleaseReleaseAPage() upcall 3. DB picks a clean page, calls DeallocPage(pa) 4. OR DB picks dirty page, writes to disk, then DeallocPage(pa) exokernel example: cpu what does it mean to expose cpu to app? kernel tells app when it is taking away cpu kernel tells app when it gives cpu to app so if app is running and timer interrupt causes end of slice cpu jumps from app into kernel kernel jumps back into app at "please yield" upcall app saves state (registers, EIP, &c) app calls Yield() when kernel decides to resume app kernel jumps into app at "resume" upcall app restores those saved registers and EIP (app knows best which registers to save. e.g., callee-saved versus caller-saved). what cool things could an app do w/ exokernel-style cpu management? suppose time slice ends in the middle of acquire(lock); ... release(lock); you don't want the app to be holding the lock the whole time! then maybe other apps can't make forward progress so the "please yield" upcall can first complete the critical section fast RPC with direct cpu management how does traditional o/s let apps communicate? pipes (or sockets) picture: buffer in kernel, lots of copying and system calls RPC probably takes 8 kernel/user crossings (read()s and write()s) [figure] how does exokernel help? Yield() can take a target process argument almost a direct jump to an instruction in target process kernel allows only entries at approved locations in target kernel leaves regs alone, so can contain arguments (in constrast to traditional restore of target's registers) target app uses Yield() to return so only 4 crossings [figure] procedure calls v/s thread switching save active caller regs call foo ---------------> save used callee registers ... do work ... restore callee registers jumps back to pc <--------- restore caller regs What state is saved proactively? What state is saved lazily? What state is not saved? Synchronous thread switching (assuming ~RISC architecture) # scheduler called by running thread (e.g., using thread_yield()) # cswitch called by scheduler: a0 holds ptr to old thread blk # a1 holds ptr to new thread blk cswitch: add sp, sp, -128 st s0, 0(sp) # save callee registers st s1, 4(sp) st s2, 8(sp) ... st ra, 124(sp) # save return address st sp, 0(a0) # save stack pointer ld sp, 0(a1) # load new stack pointer ld s0, 0(sp) # load up in reverse ld s1, 4(sp) # load up in reverse ld s2, 8(sp) # load up in reverse ... ld ra, 124(sp) # load return address add sp, sp, 128 # pop-off the stack j ra Asynchronous thread switching (assuming ~RISC architecture) # k0 = reserved register # save current state: # triggered by interrupt. save current thread. call scheduler save_state: add sp, sp, -128 st s0, 0(sp) # save callee regs st s1, 0(sp) ... st t0, 64(sp) # save caller regs st t1, 68(sp) ... st epc, 132(sp) # interrupt pc ld k0, current_thread st sp, 0(k0) ld sp, scheduler_stack j scheduler # restore current state # called by scheduler restore_state: ld k0, current_thread ld sp, 0(k0) ld s0, 0(sp) ld s1, 4(sp) ... ld t0, 64(sp) ... add sp, sp, 128 ld k0, 132(sp) # old pc j k0 Q: What is special about k0? k0 needs to be a register that is never used by the thread logic (it is not saved or restored). k0 can also be a memory location Q: Some differences from synchronous thread switching? -- Jump to scheduler performed after saving running thread registers. -- Need to save caller-saved regs too. why? Real o/s permutations based on: - one or many address spaces - one or many threads per address space # of addr spaces | 1 | many -------------------------------------------------------------------- # of threads/addr-space | | 1 | MS-DOS, Macintosh | Traditional Unix -------------------------------------------------------------------- many | Embedded systems, | VMS, Mach, OS/2, | Pilot | Win/NT, Solaris, HP-UX, | | Linux Example: web server - Server must handle many requests - Non-cooperating version: while (1) { con = AcceptConnection(); ProcessFork(ServiceWebPage(), con); } What are some disadvantages? Expensive to start new process, heavyweight context switch overhead (changing address spaces) - Web Server Using Threads: while (1) { con = AcceptConnection(); ThreadFork(ServiceWebPage(), con); } Looks almost the same but has many advantages due to shared address space among multiple threads: - Can share file caches kept in memory, results of CGI scripts, etc. - Threads are *much* cheaper to create than processes, so lower per-request overhead Q: Would a user-level (say many-to-one) thread package make sense here? When one request blocks on disk, all block ...