Changeset d677355 for doc/theses/thierry_delisle_PhD/thesis/text
- Timestamp:
- Jul 20, 2022, 2:37:25 PM (2 years ago)
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doc/theses/thierry_delisle_PhD/thesis/text/core.tex
r847bb6f rd677355 341 341 342 342 \subsection{Topological Work Stealing} 343 \label{s:TopologicalWorkStealing} 343 344 Therefore, the approach used in the \CFA scheduler is to have per-\proc subqueues, but have an explicit data-structure track which cache substructure each subqueue is tied to. 344 345 This tracking requires some finesse because reading this data structure must lead to fewer cache misses than not having the data structure in the first place. -
doc/theses/thierry_delisle_PhD/thesis/text/io.tex
r847bb6f rd677355 250 250 In this design, allocation and submission form a partitioned ring buffer as shown in Figure~\ref{fig:pring}. 251 251 Once added to the ring buffer, the attached \gls{proc} has a significant amount of flexibility with regards to when to perform the system call. 252 Possible options are: when the \gls{proc} runs out of \glspl{thrd} to run, after running a given number of \glspl{thrd}, etc.252 Possible options are: when the \gls{proc} runs out of \glspl{thrd} to run, after running a given number of \glspl{thrd}, \etc. 253 253 254 254 \begin{figure} -
doc/theses/thierry_delisle_PhD/thesis/text/practice.tex
r847bb6f rd677355 1 1 \chapter{Scheduling in practice}\label{practice} 2 The scheduling algorithm d iscribed in Chapter~\ref{core} addresses scheduling in a stable state.3 However, it does not address problems that occur when the system changes state.2 The scheduling algorithm described in Chapter~\ref{core} addresses scheduling in a stable state. 3 This chapter addresses problems that occur when the system state changes. 4 4 Indeed the \CFA runtime, supports expanding and shrinking the number of \procs, both manually and, to some extent, automatically. 5 This entails that the scheduling algorithm must support these transitions. 6 7 More precise \CFA supports adding \procs using the RAII object @processor@. 8 These objects can be created at any time and can be destroyed at any time. 9 They are normally created as automatic stack variables, but this is not a requirement. 10 11 The consequence is that the scheduler and \io subsystems must support \procs comming in and out of existence. 5 These changes affect the scheduling algorithm, which must dynamically alter its behaviour. 6 7 In detail, \CFA supports adding \procs using the type @processor@, in both RAII and heap coding scenarios. 8 \begin{lstlisting} 9 { 10 processor p[4]; // 4 new kernel threads 11 ... // execute on 4 processors 12 processor * dp = new( processor, 6 ); // 6 new kernel threads 13 ... // execute on 10 processors 14 delete( dp ); // delete 6 kernel threads 15 ... // execute on 4 processors 16 } // delete 4 kernel threads 17 \end{lstlisting} 18 Dynamically allocated processors can be deleted an any time, \ie their lifetime exceeds the block of creation. 19 The consequence is that the scheduler and \io subsystems must know when these \procs come in and out of existence and roll them into the appropriate scheduling algorithms. 12 20 13 21 \section{Manual Resizing} 14 22 Manual resizing is expected to be a rare operation. 15 Programmers are mostly expected to resize clusters on startup or teardown. 16 Therefore dynamically changing the number of \procs is an appropriate moment to allocate or free resources to match the new state. 17 As such all internal arrays that are sized based on the number of \procs need to be @realloc@ed. 18 This also means that any references into these arrays, pointers or indexes, may need to be fixed when shrinking\footnote{Indexes may still need fixing when shrinkingbecause some indexes are expected to refer to dense contiguous resources and there is no guarantee the resource being removed has the highest index.}. 23 Programmers normally create/delete processors on a clusters at startup/teardown. 24 Therefore, dynamically changing the number of \procs is an appropriate moment to allocate or free resources to match the new state. 25 As such, all internal scheduling arrays that are sized based on the number of \procs need to be @realloc@ed. 26 This requirement also means any references into these arrays, \eg pointers or indexes, may need to be updated if elements are moved for compaction or any other reason. 27 % \footnote{Indexes may still need fixing when shrinking because some indexes are expected to refer to dense contiguous resources and there is no guarantee the resource being removed has the highest index.} 19 28 20 29 There are no performance requirements, within reason, for resizing since it is expected to be rare. 21 However, this operation has strict correctness requirements since shrinking and idle sleep can easily lead to deadlocks.30 However, this operation has strict correctness requirements since updating and idle sleep can easily lead to deadlocks. 22 31 It should also avoid as much as possible any effect on performance when the number of \procs remain constant. 23 32 This later requirement prohibits naive solutions, like simply adding a global lock to the ready-queue arrays. 24 33 25 34 \subsection{Read-Copy-Update} 26 One solution is to use the Read-Copy-Update\cite{wiki:rcu} pattern. 27 In this pattern, resizing is done by creating a copy of the internal data strucures, updating the copy with the desired changes, and then attempt an Idiana Jones Switch to replace the original witht the copy. 28 This approach potentially has the advantage that it may not need any synchronization to do the switch. 29 However, there is a race where \procs could still use the previous, original, data structure after the copy was switched in. 30 This race not only requires some added memory reclamation scheme, it also requires that operations made on the stale original version be eventually moved to the copy. 31 32 For linked-lists, enqueing is only somewhat problematic, \ats enqueued to the original queues need to be transferred to the new, which might not preserve ordering. 33 Dequeing is more challenging. 34 Dequeing from the original will not necessarily update the copy which could lead to multiple \procs dequeing the same \at. 35 Fixing this requires more synchronization or more indirection on the queues. 36 37 Another challenge is that the original must be kept until all \procs have witnessed the change. 38 This is a straight forward memory reclamation challenge but it does mean that every operation will need \emph{some} form of synchronization. 39 If each of these operation does need synchronization then it is possible a simpler solution achieves the same performance. 40 Because in addition to the classic challenge of memory reclamation, transferring the original data to the copy before reclaiming it poses additional challenges. 35 One solution is to use the Read-Copy-Update pattern~\cite{wiki:rcu}. 36 In this pattern, resizing is done by creating a copy of the internal data structures (\eg see Figure~\ref{fig:base-ts2}), updating the copy with the desired changes, and then attempt an Indiana Jones Switch to replace the original with the copy. 37 This approach has the advantage that it may not need any synchronization to do the switch. 38 However, there is a race where \procs still use the original data structure after the copy is switched. 39 This race not only requires adding a memory-reclamation scheme, it also requires that operations made on the stale original version are eventually moved to the copy. 40 41 Specifically, the original data structure must be kept until all \procs have witnessed the change. 42 This requirement is the \newterm{memory reclamation challenge} and means every operation needs \emph{some} form of synchronization. 43 If all operations need synchronization, then the overall cost of this technique is likely to be similar to an uncontended lock approach. 44 In addition to the classic challenge of memory reclamation, transferring the original data to the copy before reclaiming it poses additional challenges. 41 45 Especially merging subqueues while having a minimal impact on fairness and locality. 42 46 43 \subsection{Read-Writer Lock} 44 A simpler approach would be to use a \newterm{Readers-Writer Lock}\cite{wiki:rwlock} where the resizing requires acquiring the lock as a writer while simply enqueing/dequeing \ats requires acquiring the lock as a reader. 47 For example, given a linked-list, having a node enqueued onto the original and new list is not necessarily a problem depending on the chosen list structure. 48 If the list supports arbitrary insertions, then inconsistencies in the tail pointer do not break the list; 49 however, ordering may not be preserved. 50 Furthermore, nodes enqueued to the original queues eventually need to be uniquely transferred to the new queues, which may further perturb ordering. 51 Dequeuing is more challenging when nodes appear on both lists because of pending reclamation: dequeuing a node from one list does not remove it from the other nor is that node in the same place on the other list. 52 This situation can lead to multiple \procs dequeuing the same \at. 53 Fixing these challenges requires more synchronization or more indirection to the queues, plus coordinated searching to ensure unique elements. 54 55 \subsection{Readers-Writer Lock} 56 A simpler approach is to use a \newterm{Readers-Writer Lock}~\cite{wiki:rwlock}, where the resizing requires acquiring the lock as a writer while simply enqueueing/dequeuing \ats requires acquiring the lock as a reader. 45 57 Using a Readers-Writer lock solves the problem of dynamically resizing and leaves the challenge of finding or building a lock with sufficient good read-side performance. 46 Since this is not a very complex challenge and an ad-hoc solution is perfectly acceptable, building a Readers-Writer lock was the path taken. 47 48 To maximize reader scalability, the readers should not contend with eachother when attempting to acquire and release the critical sections. 49 This effectively requires that each reader have its own piece of memory to mark as locked and unlocked. 50 Reades then acquire the lock wait for writers to finish the critical section and then acquire their local spinlocks. 51 Writers acquire the global lock, so writers have mutual exclusion among themselves, and then acquires each of the local reader locks. 52 Acquiring all the local locks guarantees mutual exclusion between the readers and the writer, while the wait on the read side prevents readers from continously starving the writer. 53 \todo{reference listings} 54 58 Since this approach is not a very complex challenge and an ad-hoc solution is perfectly acceptable, building a Readers-Writer lock was the path taken. 59 60 To maximize reader scalability, readers should not contend with each other when attempting to acquire and release a critical section. 61 To achieve this goal requires each reader to have its own memory to mark as locked and unlocked. 62 The read acquire possibly waits for a writer to finish the critical section and then acquires a reader's local spinlock. 63 The write acquire acquires the global lock, guaranteeing mutual exclusion among writers, and then acquires each of the local reader locks. 64 Acquiring all the local read locks guarantees mutual exclusion among the readers and the writer, while the wait on the read side prevents readers from continuously starving the writer. 65 66 Figure~\ref{f:SpecializedReadersWriterLock} shows the outline for this specialized readers-writer lock. 67 The lock in nonblocking, so both readers and writers spin while the lock is held. 68 \todo{finish explanation} 69 70 \begin{figure} 55 71 \begin{lstlisting} 56 72 void read_lock() { 57 73 // Step 1 : make sure no writers in 58 74 while write_lock { Pause(); } 59 60 // May need fence here61 62 75 // Step 2 : acquire our local lock 63 while atomic_xchg( tls.lock ) { 64 Pause(); 65 } 66 } 67 76 while atomic_xchg( tls.lock ) { Pause(); } 77 } 68 78 void read_unlock() { 69 79 tls.lock = false; 70 80 } 71 \end{lstlisting}72 73 \begin{lstlisting}74 81 void write_lock() { 75 82 // Step 1 : lock global lock 76 while atomic_xchg( write_lock ) { 77 Pause(); 78 } 79 83 while atomic_xchg( write_lock ) { Pause(); } 80 84 // Step 2 : lock per-proc locks 81 85 for t in all_tls { 82 while atomic_xchg( t.lock ) { 83 Pause(); 84 } 86 while atomic_xchg( t.lock ) { Pause(); } 85 87 } 86 88 } 87 88 89 void write_unlock() { 89 90 // Step 1 : release local locks 90 for t in all_tls { 91 t.lock = false; 92 } 93 91 for t in all_tls { t.lock = false; } 94 92 // Step 2 : release global lock 95 93 write_lock = false; 96 94 } 97 95 \end{lstlisting} 96 \caption{Specialized Readers-Writer Lock} 97 \label{f:SpecializedReadersWriterLock} 98 \end{figure} 98 99 99 100 \section{Idle-Sleep} 100 In addition to users manually changing the number of \procs, it is desireable to support ``removing'' \procs when there is not enough \ats for all the \procs to be useful. 101 While manual resizing is expected to be rare, the number of \ats is expected to vary much more which means \procs may need to be ``removed'' for only short periods of time. 102 Furthermore, race conditions that spuriously lead to the impression that no \ats are ready are actually common in practice. 103 Therefore resources associated with \procs should not be freed but \procs simply put into an idle state where the \gls{kthrd} is blocked until more \ats become ready. 104 This state is referred to as \newterm{Idle-Sleep}. 101 While manual resizing of \procs is expected to be rare, the number of \ats can vary significantly over an application's lifetime, which means there are times when there are too few or too many \procs. 102 For this work, it is the programer's responsibility to manually create \procs, so if there a too few \procs, the application must address this issue. 103 This leaves too many \procs when there are not enough \ats for all the \procs to be useful. 104 These idle \procs cannot be removed because their lifetime is controlled by the application, and only the application knows when the number of \ats may increase or decrease. 105 While idle \procs can spin until work appears, this approach wastes the processor (from other applications), energy and heat. 106 Therefore, idle \procs are put into an idle state, called \newterm{Idle-Sleep}, where the \gls{kthrd} is blocked until the scheduler deems it is needed. 105 107 106 108 Idle sleep effectively encompasses several challenges. 107 First somedata structure needs to keep track of all \procs that are in idle sleep.108 Because of idle sleep can be spurious, this data structure has strict performance requirements in addition to thestrict correctness requirements.109 Next, some tool must be used to block kernel threads \glspl{kthrd}, \eg @pthread_cond_wait@, pthread semaphores.110 The complexity here is to support \at parking and unparking, timers, \io operationsand all other \CFA features with minimal complexity.111 Finally, idle sleep also includes a heuristic to determine the appropriate number of \procs to be in idle sleep an any given time.112 This third challenge is however outside the scope of this thesis because developping a general heuristic is involvedenough to justify its own work.113 The \CFA scheduler simply follows the ``Race-to-Idle'\cit{https://doi.org/10.1137/1.9781611973099.100}' approach where a sleeping \proc is woken any time an\at becomes ready and \procs go to idle sleep anytime they run out of work.109 First, a data structure needs to keep track of all \procs that are in idle sleep. 110 Because idle sleep is spurious, this data structure has strict performance requirements, in addition to strict correctness requirements. 111 Next, some mechanism is needed to block \glspl{kthrd}, \eg @pthread_cond_wait@ on a pthread semaphore. 112 The complexity here is to support \at parking and unparking, user-level locking, timers, \io operations, and all other \CFA features with minimal complexity. 113 Finally, the scheduler needs a heuristic to determine when to block and unblock an appropriate number of \procs. 114 However, this third challenge is outside the scope of this thesis because developing a general heuristic is complex enough to justify its own work. 115 Therefore, the \CFA scheduler simply follows the ``Race-to-Idle''~\cite{Albers12} approach where a sleeping \proc is woken any time a \at becomes ready and \procs go to idle sleep anytime they run out of work. 114 116 115 117 \section{Sleeping} 116 118 As usual, the corner-stone of any feature related to the kernel is the choice of system call. 117 In terms of blocking a \gls{kthrd} until some event occurs the linux kernel has many available options: 118 119 \paragraph{\lstinline{pthread_mutex}/\lstinline{pthread_cond}} 120 The most classic option is to use some combination of @pthread_mutex@ and @pthread_cond@. 121 These serve as straight forward mutual exclusion and synchronization tools and allow a \gls{kthrd} to wait on a @pthread_cond@ until signalled. 122 While this approach is generally perfectly appropriate for \glspl{kthrd} waiting after eachother, \io operations do not signal @pthread_cond@s. 123 For \io results to wake a \proc waiting on a @pthread_cond@ means that a different \glspl{kthrd} must be woken up first, and then the \proc can be signalled. 119 In terms of blocking a \gls{kthrd} until some event occurs, the Linux kernel has many available options. 120 121 \subsection{\lstinline{pthread_mutex}/\lstinline{pthread_cond}} 122 The classic option is to use some combination of the pthread mutual exclusion and synchronization locks, allowing a safe park/unpark of a \gls{kthrd} to/from a @pthread_cond@. 123 While this approach works for \glspl{kthrd} waiting among themselves, \io operations do not provide a mechanism to signal @pthread_cond@s. 124 For \io results to wake a \proc waiting on a @pthread_cond@ means a different \glspl{kthrd} must be woken up first, which then signals the \proc. 124 125 125 126 \subsection{\lstinline{io_uring} and Epoll} 126 An alternative is to flip the problem on its head and block waiting for \io, using @io_uring@ or even@epoll@.127 This creates the inverse situation, where \io operations directly wake sleeping \procs but waking \proc from a running \gls{kthrd}must use an indirect scheme.128 This generally takes the form of creating a file descriptor, \eg, a dummy file, a pipe or an event fd, and using that file descriptor when \procs need to wake eachother.129 This leads to additional complexity because there can be a race between these artificial \io operationsand genuine \io operations.130 If not handled correctly, this can lead to the artificial files going out of sync.127 An alternative is to flip the problem on its head and block waiting for \io, using @io_uring@ or @epoll@. 128 This creates the inverse situation, where \io operations directly wake sleeping \procs but waking blocked \procs must use an indirect scheme. 129 This generally takes the form of creating a file descriptor, \eg, dummy file, pipe, or event fd, and using that file descriptor when \procs need to wake each other. 130 This leads to additional complexity because there can be a race between these artificial \io and genuine \io operations. 131 If not handled correctly, this can lead to artificial files getting delaying too long behind genuine files, resulting in longer latency. 131 132 132 133 \subsection{Event FDs} 133 134 Another interesting approach is to use an event file descriptor\cit{eventfd}. 134 This is a Linux feature thatis a file descriptor that behaves like \io, \ie, uses @read@ and @write@, but also behaves like a semaphore.135 Indeed, all read and writes must use 64bits large values\footnote{On 64-bit Linux, a 32-bit Linux would use 32 bits values.}.136 Writes add their values to the buffer, that is arithmetic addition and not buffer append, and reads zero out the buffer and return the buffer values so far\footnote{137 This is without the \lstinline{EFD_SEMAPHORE} flag. This flags changes the behavior of \lstinline{read} but is not needed for this work.}.135 This Linux feature is a file descriptor that behaves like \io, \ie, uses @read@ and @write@, but also behaves like a semaphore. 136 Indeed, all reads and writes must use a word-sized values, \ie 64 or 32 bits. 137 Writes \emph{add} their values to a buffer using arithmetic addition versus buffer append, and reads zero out the buffer and return the buffer values so far.\footnote{ 138 This behaviour is without the \lstinline{EFD_SEMAPHORE} flag, which changes the behaviour of \lstinline{read} but is not needed for this work.} 138 139 If a read is made while the buffer is already 0, the read blocks until a non-0 value is added. 139 What makes this feature particularly interesting is that @io_uring@ supports the @IORING_REGISTER_EVENTFD@ command, to register an event fd to a particular instance. 140 Once that instance is registered, any \io completion will result in @io\_uring@ writing to the event FD. 141 This means that a \proc waiting on the event FD can be \emph{directly} woken up by either other \procs or incomming \io. 140 What makes this feature particularly interesting is that @io_uring@ supports the @IORING_REGISTER_EVENTFD@ command to register an event @fd@ to a particular instance. 141 Once that instance is registered, any \io completion results in @io_uring@ writing to the event @fd@. 142 This means that a \proc waiting on the event @fd@ can be \emph{directly} woken up by either other \procs or incoming \io. 143 144 \section{Tracking Sleepers} 145 Tracking which \procs are in idle sleep requires a data structure holding all the sleeping \procs, but more importantly it requires a concurrent \emph{handshake} so that no \at is stranded on a ready-queue with no active \proc. 146 The classic challenge occurs when a \at is made ready while a \proc is going to sleep: there is a race where the new \at may not see the sleeping \proc and the sleeping \proc may not see the ready \at. 147 Since \ats can be made ready by timers, \io operations, or other events outside a cluster, this race can occur even if the \proc going to sleep is the only \proc awake. 148 As a result, improper handling of this race leads to all \procs going to sleep when there are ready \ats and the system deadlocks. 149 150 Furthermore, the ``Race-to-Idle'' approach means that there may be contention on the data structure tracking sleepers. 151 Contention can be tolerated for \procs attempting to sleep or wake-up because these \procs are not doing useful work, and therefore, not contributing to overall performance. 152 However, notifying, checking if a \proc must be woken-up, and doing so if needed, can significantly affect overall performance and must be low cost. 153 154 \subsection{Sleepers List} 155 Each cluster maintains a list of idle \procs, organized as a stack. 156 This ordering allows \procs at the head of the list to stay constantly active and those at the tail to stay in idle sleep for extended period of times. 157 Because of unbalanced performance requirements, the algorithm tracking sleepers is designed to have idle \procs handle as much of the work as possible. 158 The idle \procs maintain the stack of sleepers among themselves and notifying a sleeping \proc takes as little work as possible. 159 This approach means that maintaining the list is fairly straightforward. 160 The list can simply use a single lock per cluster and only \procs that are getting in and out of the idle state contend for that lock. 161 162 This approach also simplifies notification. 163 Indeed, \procs not only need to be notify when a new \at is readied, but also must be notified during manual resizing, so the \gls{kthrd} can be joined. 164 These requirements mean whichever entity removes idle \procs from the sleeper list must be able to do so in any order. 165 Using a simple lock over this data structure makes the removal much simpler than using a lock-free data structure. 166 The single lock also means the notification process simply needs to wake-up the desired idle \proc, using @pthread_cond_signal@, @write@ on an @fd@, \etc, and the \proc handles the rest. 167 168 \subsection{Reducing Latency} 169 As mentioned in this section, \procs going to sleep for extremely short periods of time is likely in certain scenarios. 170 Therefore, the latency of doing a system call to read from and writing to an event @fd@ can negatively affect overall performance in a notable way. 171 Hence, it is important to reduce latency and contention of the notification as much as possible. 172 Figure~\ref{fig:idle1} shows the basic idle-sleep data structure. 173 For the notifiers, this data structure can cause contention on the lock and the event @fd@ syscall can cause notable latency. 142 174 143 175 \begin{figure} … … 145 177 \input{idle1.pstex_t} 146 178 \caption[Basic Idle Sleep Data Structure]{Basic Idle Sleep Data Structure \smallskip\newline Each idle \proc is put unto a doubly-linked stack protected by a lock. 147 Each \proc has a private event FD.}179 Each \proc has a private event \lstinline{fd}.} 148 180 \label{fig:idle1} 149 181 \end{figure} 150 182 151 152 \section{Tracking Sleepers} 153 Tracking which \procs are in idle sleep requires a data structure holding all the sleeping \procs, but more importantly it requires a concurrent \emph{handshake} so that no \at is stranded on a ready-queue with no active \proc. 154 The classic challenge is when a \at is made ready while a \proc is going to sleep, there is a race where the new \at may not see the sleeping \proc and the sleeping \proc may not see the ready \at. 155 Since \ats can be made ready by timers, \io operations or other events outside a clusre, this race can occur even if the \proc going to sleep is the only \proc awake. 156 As a result, improper handling of this race can lead to all \procs going to sleep and the system deadlocking. 157 158 Furthermore, the ``Race-to-Idle'' approach means that there may be contention on the data structure tracking sleepers. 159 Contention slowing down \procs attempting to sleep or wake-up can be tolerated. 160 These \procs are not doing useful work and therefore not contributing to overall performance. 161 However, notifying, checking if a \proc must be woken-up and doing so if needed, can significantly affect overall performance and must be low cost. 162 163 \subsection{Sleepers List} 164 Each cluster maintains a list of idle \procs, organized as a stack. 165 This ordering hopefully allows \proc at the tail to stay in idle sleep for extended period of times. 166 Because of these unbalanced performance requirements, the algorithm tracking sleepers is designed to have idle \proc handle as much of the work as possible. 167 The idle \procs maintain the of sleepers among themselves and notifying a sleeping \proc takes as little work as possible. 168 This approach means that maintaining the list is fairly straightforward. 169 The list can simply use a single lock per cluster and only \procs that are getting in and out of idle state will contend for that lock. 170 171 This approach also simplifies notification. 172 Indeed, \procs need to be notify when a new \at is readied, but they also must be notified during resizing, so the \gls{kthrd} can be joined. 173 This means that whichever entity removes idle \procs from the sleeper list must be able to do so in any order. 174 Using a simple lock over this data structure makes the removal much simpler than using a lock-free data structure. 175 The notification process then simply needs to wake-up the desired idle \proc, using @pthread_cond_signal@, @write@ on an fd, etc., and the \proc will handle the rest. 176 177 \subsection{Reducing Latency} 178 As mentioned in this section, \procs going idle for extremely short periods of time is likely in certain common scenarios. 179 Therefore, the latency of doing a system call to read from and writing to the event fd can actually negatively affect overall performance in a notable way. 180 Is it important to reduce latency and contention of the notification as much as possible. 181 Figure~\ref{fig:idle1} shoes the basic idle sleep data structure. 182 For the notifiers, this data structure can cause contention on the lock and the event fd syscall can cause notable latency. 183 184 \begin{figure} 183 Contention occurs because the idle-list lock must be held to access the idle list, \eg by \procs attempting to go to sleep, \procs waking, or notification attempts. 184 The contention from the \procs attempting to go to sleep can be mitigated slightly by using @try_acquire@, so the \procs simply busy wait again searching for \ats if the lock is held. 185 This trick cannot be used when waking \procs since the waker needs to return immediately to what it was doing. 186 Interestingly, general notification, \ie waking any idle processor versus a specific one, does not strictly require modifying the list. 187 Here, contention can be reduced notably by having notifiers avoid the lock entirely by adding a pointer to the event @fd@ of the first idle \proc, as in Figure~\ref{fig:idle2}. 188 To avoid contention among notifiers, notifiers atomically exchange it to @NULL@ so only one notifier contends on the system call. 189 \todo{Expand explanation of how a notification works.} 190 191 \begin{figure}[t] 185 192 \centering 186 193 \input{idle2.pstex_t} 187 \caption[Improved Idle Sleep Data Structure]{Improved Idle Sleep Data Structure \smallskip\newline An atomic pointer is added to the list,pointing to the Event FD of the first \proc on the list.}194 \caption[Improved Idle-Sleep Data Structure]{Improved Idle-Sleep Data Structure \smallskip\newline An atomic pointer is added to the list pointing to the Event FD of the first \proc on the list.} 188 195 \label{fig:idle2} 189 196 \end{figure} 190 197 191 The contention is mostly due to the lock on the list needing to be held to get to the head \proc. 192 That lock can be contended by \procs attempting to go to sleep, \procs waking or notification attempts. 193 The contentention from the \procs attempting to go to sleep can be mitigated slightly by using @try\_acquire@ instead, so the \procs simply continue searching for \ats if the lock is held. 194 This trick cannot be used for waking \procs since they are not in a state where they can run \ats. 195 However, it is worth nothing that notification does not strictly require accessing the list or the head \proc. 196 Therefore, contention can be reduced notably by having notifiers avoid the lock entirely and adding a pointer to the event fd of the first idle \proc, as in Figure~\ref{fig:idle2}. 197 To avoid contention between the notifiers, instead of simply reading the atomic pointer, notifiers atomically exchange it to @null@ so only only notifier will contend on the system call. 198 The next optimization is to avoid the latency of the event @fd@, which can be done by adding what is effectively a benaphore\cit{benaphore} in front of the event @fd@. 199 A simple three state flag is added beside the event @fd@ to avoid unnecessary system calls, as shown in Figure~\ref{fig:idle:state}. 200 In Topological Work Stealing (see Section~\ref{s:TopologicalWorkStealing}), a \proc without \ats begins searching by setting the state flag to @SEARCH@. 201 If no \ats can be found to steal, the \proc then confirms it is going to sleep by atomically swapping the state to @SLEEP@. 202 If the previous state is still @SEARCH@, then the \proc does read the event @fd@. 203 Meanwhile, notifiers atomically exchange the state to @AWAKE@ state. 204 If the previous state is @SLEEP@, then the notifier must write to the event @fd@. 205 However, if the notify arrives almost immediately after the \proc marks itself sleeping (idle), then both reads and writes on the event @fd@ can be omitted, which reduces latency notably. 206 These extensions leads to the final data structure shown in Figure~\ref{fig:idle}. 207 \todo{You never talk about the Beaphore. What is its purpose and when is it used?} 198 208 199 209 \begin{figure} 200 210 \centering 201 211 \input{idle_state.pstex_t} 202 \caption[Improved Idle Sleep Data Structure]{Improved Idle Sleep Data Structure \smallskip\newline An atomic pointer is added to the list, pointing to the Event FD of the first \proc on the list.}212 \caption[Improved Idle-Sleep Latency]{Improved Idle-Sleep Latency \smallskip\newline A three state flag is added to the event \lstinline{fd}.} 203 213 \label{fig:idle:state} 204 214 \end{figure} 205 206 The next optimization that can be done is to avoid the latency of the event fd when possible.207 This can be done by adding what is effectively a benaphore\cit{benaphore} in front of the event fd.208 A simple three state flag is added beside the event fd to avoid unnecessary system calls, as shown in Figure~\ref{fig:idle:state}.209 The flag starts in state @SEARCH@, while the \proc is searching for \ats to run.210 The \proc then confirms the sleep by atomically swaping the state to @SLEEP@.211 If the previous state was still @SEARCH@, then the \proc does read the event fd.212 Meanwhile, notifiers atomically exchange the state to @AWAKE@ state.213 if the previous state was @SLEEP@, then the notifier must write to the event fd.214 However, if the notify arrives almost immediately after the \proc marks itself idle, then both reads and writes on the event fd can be omitted, which reduces latency notably.215 This leads to the final data structure shown in Figure~\ref{fig:idle}.216 215 217 216 \begin{figure} … … 219 218 \input{idle.pstex_t} 220 219 \caption[Low-latency Idle Sleep Data Structure]{Low-latency Idle Sleep Data Structure \smallskip\newline Each idle \proc is put unto a doubly-linked stack protected by a lock. 221 Each \proc has a private event FDwith a benaphore in front of it.222 The list also has an atomic pointer to the event fdand benaphore of the first \proc on the list.}220 Each \proc has a private event \lstinline{fd} with a benaphore in front of it. 221 The list also has an atomic pointer to the event \lstinline{fd} and benaphore of the first \proc on the list.} 223 222 \label{fig:idle} 224 223 \end{figure}
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