40. Performance Thread Sample Application

The performance thread sample application is a derivative of the standard L3 forwarding application that demonstrates different threading models.

40.1. Overview

For a general description of the L3 forwarding applications capabilities please refer to the documentation of the standard application in L3 Forwarding Sample Application.

The performance thread sample application differs from the standard L3 forwarding example in that it divides the TX and RX processing between different threads, and makes it possible to assign individual threads to different cores.

Three threading models are considered:

  1. When there is one EAL thread per physical core.
  2. When there are multiple EAL threads per physical core.
  3. When there are multiple lightweight threads per EAL thread.

Since DPDK release 2.0 it is possible to launch applications using the --lcores EAL parameter, specifying cpu-sets for a physical core. With the performance thread sample application its is now also possible to assign individual RX and TX functions to different cores.

As an alternative to dividing the L3 forwarding work between different EAL threads the performance thread sample introduces the possibility to run the application threads as lightweight threads (L-threads) within one or more EAL threads.

In order to facilitate this threading model the example includes a primitive cooperative scheduler (L-thread) subsystem. More details of the L-thread subsystem can be found in The L-thread subsystem.

Note: Whilst theoretically possible it is not anticipated that multiple L-thread schedulers would be run on the same physical core, this mode of operation should not be expected to yield useful performance and is considered invalid.

40.2. Compiling the Application

The application is located in the sample application folder in the performance-thread folder.

  1. Go to the example applications folder

    export RTE_SDK=/path/to/rte_sdk
    cd ${RTE_SDK}/examples/performance-thread/l3fwd-thread
  2. Set the target (a default target is used if not specified). For example:

    export RTE_TARGET=x86_64-native-linuxapp-gcc

    See the DPDK Linux Getting Started Guide for possible RTE_TARGET values.

  3. Build the application:


40.3. Running the Application

The application has a number of command line options:

./build/l3fwd-thread [EAL options] --
    -p PORTMASK [-P]
    [--enable-jumbo] [--max-pkt-len PKTLEN]]  [--no-numa]
    [--hash-entry-num] [--ipv6] [--no-lthreads] [--stat-lcore lcore]


  • -p PORTMASK: Hexadecimal bitmask of ports to configure.
  • -P: optional, sets all ports to promiscuous mode so that packets are accepted regardless of the packet’s Ethernet MAC destination address. Without this option, only packets with the Ethernet MAC destination address set to the Ethernet address of the port are accepted.
  • --rx (port,queue,lcore,thread)[,(port,queue,lcore,thread)]: the list of NIC RX ports and queues handled by the RX lcores and threads. The parameters are explained below.
  • --tx (lcore,thread)[,(lcore,thread)]: the list of TX threads identifying the lcore the thread runs on, and the id of RX thread with which it is associated. The parameters are explained below.
  • --enable-jumbo: optional, enables jumbo frames.
  • --max-pkt-len: optional, maximum packet length in decimal (64-9600).
  • --no-numa: optional, disables numa awareness.
  • --hash-entry-num: optional, specifies the hash entry number in hex to be setup.
  • --ipv6: optional, set it if running ipv6 packets.
  • --no-lthreads: optional, disables l-thread model and uses EAL threading model. See below.
  • --stat-lcore: optional, run CPU load stats collector on the specified lcore.

The parameters of the --rx and --tx options are:

  • --rx parameters

    port RX port
    queue RX queue that will be read on the specified RX port
    lcore Core to use for the thread
    thread Thread id (continuously from 0 to N)
  • --tx parameters

    lcore Core to use for L3 route match and transmit
    thread Id of RX thread to be associated with this TX thread

The l3fwd-thread application allows you to start packet processing in two threading models: L-Threads (default) and EAL Threads (when the --no-lthreads parameter is used). For consistency all parameters are used in the same way for both models.

40.3.1. Running with L-threads

When the L-thread model is used (default option), lcore and thread parameters in --rx/--tx are used to affinitize threads to the selected scheduler.

For example, the following places every l-thread on different lcores:

l3fwd-thread -c ff -n 2 -- -P -p 3 \
             --rx="(0,0,0,0)(1,0,1,1)" \

The following places RX l-threads on lcore 0 and TX l-threads on lcore 1 and 2 and so on:

l3fwd-thread -c ff -n 2 -- -P -p 3 \
             --rx="(0,0,0,0)(1,0,0,1)" \

40.3.2. Running with EAL threads

When the --no-lthreads parameter is used, the L-threading model is turned off and EAL threads are used for all processing. EAL threads are enumerated in the same way as L-threads, but the --lcores EAL parameter is used to affinitize threads to the selected cpu-set (scheduler). Thus it is possible to place every RX and TX thread on different lcores.

For example, the following places every EAL thread on different lcores:

l3fwd-thread -c ff -n 2 -- -P -p 3 \
             --rx="(0,0,0,0)(1,0,1,1)" \
             --tx="(2,0)(3,1)" \

To affinitize two or more EAL threads to one cpu-set, the EAL --lcores parameter is used.

The following places RX EAL threads on lcore 0 and TX EAL threads on lcore 1 and 2 and so on:

l3fwd-thread -c ff -n 2 --lcores="(0,1)@0,(2,3)@1" -- -P -p 3 \
             --rx="(0,0,0,0)(1,0,1,1)" \
             --tx="(2,0)(3,1)" \

40.3.3. Examples

For selected scenarios the command line configuration of the application for L-threads and its corresponding EAL threads command line can be realized as follows:

  1. Start every thread on different scheduler (1:1):

    l3fwd-thread -c ff -n 2 -- -P -p 3 \
                 --rx="(0,0,0,0)(1,0,1,1)" \

    EAL thread equivalent:

    l3fwd-thread -c ff -n 2 -- -P -p 3 \
                 --rx="(0,0,0,0)(1,0,1,1)" \
                 --tx="(2,0)(3,1)" \
  2. Start all threads on one core (N:1).

    Start 4 L-threads on lcore 0:

    l3fwd-thread -c ff -n 2 -- -P -p 3 \
                 --rx="(0,0,0,0)(1,0,0,1)" \

    Start 4 EAL threads on cpu-set 0:

    l3fwd-thread -c ff -n 2 --lcores="(0-3)@0" -- -P -p 3 \
                 --rx="(0,0,0,0)(1,0,0,1)" \
                 --tx="(2,0)(3,1)" \
  3. Start threads on different cores (N:M).

    Start 2 L-threads for RX on lcore 0, and 2 L-threads for TX on lcore 1:

    l3fwd-thread -c ff -n 2 -- -P -p 3 \
                 --rx="(0,0,0,0)(1,0,0,1)" \

    Start 2 EAL threads for RX on cpu-set 0, and 2 EAL threads for TX on cpu-set 1:

    l3fwd-thread -c ff -n 2 --lcores="(0-1)@0,(2-3)@1" -- -P -p 3 \
                 --rx="(0,0,0,0)(1,0,1,1)" \
                 --tx="(2,0)(3,1)" \

40.4. Explanation

To a great extent the sample application differs little from the standard L3 forwarding application, and readers are advised to familiarize themselves with the material covered in the L3 Forwarding Sample Application documentation before proceeding.

The following explanation is focused on the way threading is handled in the performance thread example.

40.4.1. Mode of operation with EAL threads

The performance thread sample application has split the RX and TX functionality into two different threads, and the RX and TX threads are interconnected via software rings. With respect to these rings the RX threads are producers and the TX threads are consumers.

On initialization the TX and RX threads are started according to the command line parameters.

The RX threads poll the network interface queues and post received packets to a TX thread via a corresponding software ring.

The TX threads poll software rings, perform the L3 forwarding hash/LPM match, and assemble packet bursts before performing burst transmit on the network interface.

As with the standard L3 forward application, burst draining of residual packets is performed periodically with the period calculated from elapsed time using the timestamps counter.

The diagram below illustrates a case with two RX threads and three TX threads.

40.4.2. Mode of operation with L-threads

Like the EAL thread configuration the application has split the RX and TX functionality into different threads, and the pairs of RX and TX threads are interconnected via software rings.

On initialization an L-thread scheduler is started on every EAL thread. On all but the master EAL thread only a a dummy L-thread is initially started. The L-thread started on the master EAL thread then spawns other L-threads on different L-thread schedulers according the the command line parameters.

The RX threads poll the network interface queues and post received packets to a TX thread via the corresponding software ring.

The ring interface is augmented by means of an L-thread condition variable that enables the TX thread to be suspended when the TX ring is empty. The RX thread signals the condition whenever it posts to the TX ring, causing the TX thread to be resumed.

Additionally the TX L-thread spawns a worker L-thread to take care of polling the software rings, whilst it handles burst draining of the transmit buffer.

The worker threads poll the software rings, perform L3 route lookup and assemble packet bursts. If the TX ring is empty the worker thread suspends itself by waiting on the condition variable associated with the ring.

Burst draining of residual packets, less than the burst size, is performed by the TX thread which sleeps (using an L-thread sleep function) and resumes periodically to flush the TX buffer.

This design means that L-threads that have no work, can yield the CPU to other L-threads and avoid having to constantly poll the software rings.

The diagram below illustrates a case with two RX threads and three TX functions (each comprising a thread that processes forwarding and a thread that periodically drains the output buffer of residual packets).

40.4.3. CPU load statistics

It is possible to display statistics showing estimated CPU load on each core. The statistics indicate the percentage of CPU time spent: processing received packets (forwarding), polling queues/rings (waiting for work), and doing any other processing (context switch and other overhead).

When enabled statistics are gathered by having the application threads set and clear flags when they enter and exit pertinent code sections. The flags are then sampled in real time by a statistics collector thread running on another core. This thread displays the data in real time on the console.

This feature is enabled by designating a statistics collector core, using the --stat-lcore parameter.

40.5. The L-thread subsystem

The L-thread subsystem resides in the examples/performance-thread/common directory and is built and linked automatically when building the l3fwd-thread example.

The subsystem provides a simple cooperative scheduler to enable arbitrary functions to run as cooperative threads within a single EAL thread. The subsystem provides a pthread like API that is intended to assist in reuse of legacy code written for POSIX pthreads.

The following sections provide some detail on the features, constraints, performance and porting considerations when using L-threads.

40.5.1. Comparison between L-threads and POSIX pthreads

The fundamental difference between the L-thread and pthread models is the way in which threads are scheduled. The simplest way to think about this is to consider the case of a processor with a single CPU. To run multiple threads on a single CPU, the scheduler must frequently switch between the threads, in order that each thread is able to make timely progress. This is the basis of any multitasking operating system.

This section explores the differences between the pthread model and the L-thread model as implemented in the provided L-thread subsystem. If needed a theoretical discussion of preemptive vs cooperative multi-threading can be found in any good text on operating system design. Scheduling and context switching

The POSIX pthread library provides an application programming interface to create and synchronize threads. Scheduling policy is determined by the host OS, and may be configurable. The OS may use sophisticated rules to determine which thread should be run next, threads may suspend themselves or make other threads ready, and the scheduler may employ a time slice giving each thread a maximum time quantum after which it will be preempted in favor of another thread that is ready to run. To complicate matters further threads may be assigned different scheduling priorities.

By contrast the L-thread subsystem is considerably simpler. Logically the L-thread scheduler performs the same multiplexing function for L-threads within a single pthread as the OS scheduler does for pthreads within an application process. The L-thread scheduler is simply the main loop of a pthread, and in so far as the host OS is concerned it is a regular pthread just like any other. The host OS is oblivious about the existence of and not at all involved in the scheduling of L-threads.

The other and most significant difference between the two models is that L-threads are scheduled cooperatively. L-threads cannot not preempt each other, nor can the L-thread scheduler preempt a running L-thread (i.e. there is no time slicing). The consequence is that programs implemented with L-threads must possess frequent rescheduling points, meaning that they must explicitly and of their own volition return to the scheduler at frequent intervals, in order to allow other L-threads an opportunity to proceed.

In both models switching between threads requires that the current CPU context is saved and a new context (belonging to the next thread ready to run) is restored. With pthreads this context switching is handled transparently and the set of CPU registers that must be preserved between context switches is as per an interrupt handler.

An L-thread context switch is achieved by the thread itself making a function call to the L-thread scheduler. Thus it is only necessary to preserve the callee registers. The caller is responsible to save and restore any other registers it is using before a function call, and restore them on return, and this is handled by the compiler. For X86_64 on both Linux and BSD the System V calling convention is used, this defines registers RSP, RBP, and R12-R15 as callee-save registers (for more detailed discussion a good reference is X86 Calling Conventions).

Taking advantage of this, and due to the absence of preemption, an L-thread context switch is achieved with less than 20 load/store instructions.

The scheduling policy for L-threads is fixed, there is no prioritization of L-threads, all L-threads are equal and scheduling is based on a FIFO ready queue.

An L-thread is a struct containing the CPU context of the thread (saved on context switch) and other useful items. The ready queue contains pointers to threads that are ready to run. The L-thread scheduler is a simple loop that polls the ready queue, reads from it the next thread ready to run, which it resumes by saving the current context (the current position in the scheduler loop) and restoring the context of the next thread from its thread struct. Thus an L-thread is always resumed at the last place it yielded.

A well behaved L-thread will call the context switch regularly (at least once in its main loop) thus returning to the scheduler’s own main loop. Yielding inserts the current thread at the back of the ready queue, and the process of servicing the ready queue is repeated, thus the system runs by flipping back and forth the between L-threads and scheduler loop.

In the case of pthreads, the preemptive scheduling, time slicing, and support for thread prioritization means that progress is normally possible for any thread that is ready to run. This comes at the price of a relatively heavier context switch and scheduling overhead.

With L-threads the progress of any particular thread is determined by the frequency of rescheduling opportunities in the other L-threads. This means that an errant L-thread monopolizing the CPU might cause scheduling of other threads to be stalled. Due to the lower cost of context switching, however, voluntary rescheduling to ensure progress of other threads, if managed sensibly, is not a prohibitive overhead, and overall performance can exceed that of an application using pthreads. Mutual exclusion

With pthreads preemption means that threads that share data must observe some form of mutual exclusion protocol.

The fact that L-threads cannot preempt each other means that in many cases mutual exclusion devices can be completely avoided.

Locking to protect shared data can be a significant bottleneck in multi-threaded applications so a carefully designed cooperatively scheduled program can enjoy significant performance advantages.

So far we have considered only the simplistic case of a single core CPU, when multiple CPUs are considered things are somewhat more complex.

First of all it is inevitable that there must be multiple L-thread schedulers, one running on each EAL thread. So long as these schedulers remain isolated from each other the above assertions about the potential advantages of cooperative scheduling hold true.

A configuration with isolated cooperative schedulers is less flexible than the pthread model where threads can be affinitized to run on any CPU. With isolated schedulers scaling of applications to utilize fewer or more CPUs according to system demand is very difficult to achieve.

The L-thread subsystem makes it possible for L-threads to migrate between schedulers running on different CPUs. Needless to say if the migration means that threads that share data end up running on different CPUs then this will introduce the need for some kind of mutual exclusion system.

Of course rte_ring software rings can always be used to interconnect threads running on different cores, however to protect other kinds of shared data structures, lock free constructs or else explicit locking will be required. This is a consideration for the application design.

In support of this extended functionality, the L-thread subsystem implements thread safe mutexes and condition variables.

The cost of affinitizing and of condition variable signaling is significantly lower than the equivalent pthread operations, and so applications using these features will see a performance benefit. Thread local storage

As with applications written for pthreads an application written for L-threads can take advantage of thread local storage, in this case local to an L-thread. An application may save and retrieve a single pointer to application data in the L-thread struct.

For legacy and backward compatibility reasons two alternative methods are also offered, the first is modelled directly on the pthread get/set specific APIs, the second approach is modelled on the RTE_PER_LCORE macros, whereby PER_LTHREAD macros are introduced, in both cases the storage is local to the L-thread.

40.5.2. Constraints and performance implications when using L-threads API compatibility

The L-thread subsystem provides a set of functions that are logically equivalent to the corresponding functions offered by the POSIX pthread library, however not all pthread functions have a corresponding L-thread equivalent, and not all features available to pthreads are implemented for L-threads.

The pthread library offers considerable flexibility via programmable attributes that can be associated with threads, mutexes, and condition variables.

By contrast the L-thread subsystem has fixed functionality, the scheduler policy cannot be varied, and L-threads cannot be prioritized. There are no variable attributes associated with any L-thread objects. L-threads, mutexes and conditional variables, all have fixed functionality. (Note: reserved parameters are included in the APIs to facilitate possible future support for attributes).

The table below lists the pthread and equivalent L-thread APIs with notes on differences and/or constraints. Where there is no L-thread entry in the table, then the L-thread subsystem provides no equivalent function.

Table 40.3 Pthread and equivalent L-thread APIs.
Pthread function L-thread function Notes
pthread_cond_broadcast lthread_cond_broadcast See note 1
pthread_cond_destroy lthread_cond_destroy  
pthread_cond_init lthread_cond_init  
pthread_cond_signal lthread_cond_signal See note 1
pthread_cond_wait lthread_cond_wait See note 5
pthread_create lthread_create See notes 2, 3
pthread_detach lthread_detach See note 4
pthread_exit lthread_exit  
pthread_getspecific lthread_getspecific  
pthread_join lthread_join  
pthread_key_create lthread_key_create  
pthread_key_delete lthread_key_delete  
pthread_mutex_destroy lthread_mutex_destroy  
pthread_mutex_init lthread_mutex_init  
pthread_mutex_lock lthread_mutex_lock See note 6
pthread_mutex_trylock lthread_mutex_trylock See note 6
pthread_mutex_unlock lthread_mutex_unlock  
pthread_self lthread_current  
pthread_setspecific lthread_setspecific  
pthread_spin_init   See note 10
pthread_spin_destroy   See note 10
pthread_spin_lock   See note 10
pthread_spin_trylock   See note 10
pthread_spin_unlock   See note 10
pthread_cancel lthread_cancel  
pthread_yield lthread_yield See note 7
pthread_setaffinity_np lthread_set_affinity See notes 2, 3, 8
  lthread_sleep See note 9
  lthread_sleep_clks See note 9

Note 1:

Neither lthread signal nor broadcast may be called concurrently by L-threads running on different schedulers, although multiple L-threads running in the same scheduler may freely perform signal or broadcast operations. L-threads running on the same or different schedulers may always safely wait on a condition variable.

Note 2:

Pthread attributes may be used to affinitize a pthread with a cpu-set. The L-thread subsystem does not support a cpu-set. An L-thread may be affinitized only with a single CPU at any time.

Note 3:

If an L-thread is intended to run on a different NUMA node than the node that creates the thread then, when calling lthread_create() it is advantageous to specify the destination core as a parameter of lthread_create(). See Memory allocation and NUMA awareness for details.

Note 4:

An L-thread can only detach itself, and cannot detach other L-threads.

Note 5:

A wait operation on a pthread condition variable is always associated with and protected by a mutex which must be owned by the thread at the time it invokes pthread_wait(). By contrast L-thread condition variables are thread safe (for waiters) and do not use an associated mutex. Multiple L-threads (including L-threads running on other schedulers) can safely wait on a L-thread condition variable. As a consequence the performance of an L-thread condition variables is typically an order of magnitude faster than its pthread counterpart.

Note 6:

Recursive locking is not supported with L-threads, attempts to take a lock recursively will be detected and rejected.

Note 7:

lthread_yield() will save the current context, insert the current thread to the back of the ready queue, and resume the next ready thread. Yielding increases ready queue backlog, see Ready queue backlog for more details about the implications of this.

N.B. The context switch time as measured from immediately before the call to lthread_yield() to the point at which the next ready thread is resumed, can be an order of magnitude faster that the same measurement for pthread_yield.

Note 8:

lthread_set_affinity() is similar to a yield apart from the fact that the yielding thread is inserted into a peer ready queue of another scheduler. The peer ready queue is actually a separate thread safe queue, which means that threads appearing in the peer ready queue can jump any backlog in the local ready queue on the destination scheduler.

The context switch time as measured from the time just before the call to lthread_set_affinity() to just after the same thread is resumed on the new scheduler can be orders of magnitude faster than the same measurement for pthread_setaffinity_np().

Note 9:

Although there is no pthread_sleep() function, lthread_sleep() and lthread_sleep_clks() can be used wherever sleep(), usleep() or nanosleep() might ordinarily be used. The L-thread sleep functions suspend the current thread, start an rte_timer and resume the thread when the timer matures. The rte_timer_manage() entry point is called on every pass of the scheduler loop. This means that the worst case jitter on timer expiry is determined by the longest period between context switches of any running L-threads.

In a synthetic test with many threads sleeping and resuming then the measured jitter is typically orders of magnitude lower than the same measurement made for nanosleep().

Note 10:

Spin locks are not provided because they are problematical in a cooperative environment, see Locks and spinlocks for a more detailed discussion on how to avoid spin locks. Thread local storage

Of the three L-thread local storage options the simplest and most efficient is storing a single application data pointer in the L-thread struct.

The PER_LTHREAD macros involve a run time computation to obtain the address of the variable being saved/retrieved and also require that the accesses are de-referenced via a pointer. This means that code that has used RTE_PER_LCORE macros being ported to L-threads might need some slight adjustment (see Thread local storage for hints about porting code that makes use of thread local storage).

The get/set specific APIs are consistent with their pthread counterparts both in use and in performance. Memory allocation and NUMA awareness

All memory allocation is from DPDK huge pages, and is NUMA aware. Each scheduler maintains its own caches of objects: lthreads, their stacks, TLS, mutexes and condition variables. These caches are implemented as unbounded lock free MPSC queues. When objects are created they are always allocated from the caches on the local core (current EAL thread).

If an L-thread has been affinitized to a different scheduler, then it can always safely free resources to the caches from which they originated (because the caches are MPSC queues).

If the L-thread has been affinitized to a different NUMA node then the memory resources associated with it may incur longer access latency.

The commonly used pattern of setting affinity on entry to a thread after it has started, means that memory allocation for both the stack and TLS will have been made from caches on the NUMA node on which the threads creator is running. This has the side effect that access latency will be sub-optimal after affinitizing.

This side effect can be mitigated to some extent (although not completely) by specifying the destination CPU as a parameter of lthread_create() this causes the L-thread’s stack and TLS to be allocated when it is first scheduled on the destination scheduler, if the destination is a on another NUMA node it results in a more optimal memory allocation.

Note that the lthread struct itself remains allocated from memory on the creating node, this is unavoidable because an L-thread is known everywhere by the address of this struct. Object cache sizing

The per lcore object caches pre-allocate objects in bulk whenever a request to allocate an object finds a cache empty. By default 100 objects are pre-allocated, this is defined by LTHREAD_PREALLOC in the public API header file lthread_api.h. This means that the caches constantly grow to meet system demand.

In the present implementation there is no mechanism to reduce the cache sizes if system demand reduces. Thus the caches will remain at their maximum extent indefinitely.

A consequence of the bulk pre-allocation of objects is that every 100 (default value) additional new object create operations results in a call to rte_malloc(). For creation of objects such as L-threads, which trigger the allocation of even more objects (i.e. their stacks and TLS) then this can cause outliers in scheduling performance.

If this is a problem the simplest mitigation strategy is to dimension the system, by setting the bulk object pre-allocation size to some large number that you do not expect to be exceeded. This means the caches will be populated once only, the very first time a thread is created. Ready queue backlog

One of the more subtle performance considerations is managing the ready queue backlog. The fewer threads that are waiting in the ready queue then the faster any particular thread will get serviced.

In a naive L-thread application with N L-threads simply looping and yielding, this backlog will always be equal to the number of L-threads, thus the cost of a yield to a particular L-thread will be N times the context switch time.

This side effect can be mitigated by arranging for threads to be suspended and wait to be resumed, rather than polling for work by constantly yielding. Blocking on a mutex or condition variable or even more obviously having a thread sleep if it has a low frequency workload are all mechanisms by which a thread can be excluded from the ready queue until it really does need to be run. This can have a significant positive impact on performance. Initialization, shutdown and dependencies

The L-thread subsystem depends on DPDK for huge page allocation and depends on the rte_timer subsystem. The DPDK EAL initialization and rte_timer_subsystem_init() MUST be completed before the L-thread sub system can be used.

Thereafter initialization of the L-thread subsystem is largely transparent to the application. Constructor functions ensure that global variables are properly initialized. Other than global variables each scheduler is initialized independently the first time that an L-thread is created by a particular EAL thread.

If the schedulers are to be run as isolated and independent schedulers, with no intention that L-threads running on different schedulers will migrate between schedulers or synchronize with L-threads running on other schedulers, then initialization consists simply of creating an L-thread, and then running the L-thread scheduler.

If there will be interaction between L-threads running on different schedulers, then it is important that the starting of schedulers on different EAL threads is synchronized.

To achieve this an additional initialization step is necessary, this is simply to set the number of schedulers by calling the API function lthread_num_schedulers_set(n), where n is the number of EAL threads that will run L-thread schedulers. Setting the number of schedulers to a number greater than 0 will cause all schedulers to wait until the others have started before beginning to schedule L-threads.

The L-thread scheduler is started by calling the function lthread_run() and should be called from the EAL thread and thus become the main loop of the EAL thread.

The function lthread_run(), will not return until all threads running on the scheduler have exited, and the scheduler has been explicitly stopped by calling lthread_scheduler_shutdown(lcore) or lthread_scheduler_shutdown_all().

All these function do is tell the scheduler that it can exit when there are no longer any running L-threads, neither function forces any running L-thread to terminate. Any desired application shutdown behavior must be designed and built into the application to ensure that L-threads complete in a timely manner.

Important Note: It is assumed when the scheduler exits that the application is terminating for good, the scheduler does not free resources before exiting and running the scheduler a subsequent time will result in undefined behavior.

40.5.3. Porting legacy code to run on L-threads

Legacy code originally written for a pthread environment may be ported to L-threads if the considerations about differences in scheduling policy, and constraints discussed in the previous sections can be accommodated.

This section looks in more detail at some of the issues that may have to be resolved when porting code. pthread API compatibility

The first step is to establish exactly which pthread APIs the legacy application uses, and to understand the requirements of those APIs. If there are corresponding L-lthread APIs, and where the default pthread functionality is used by the application then, notwithstanding the other issues discussed here, it should be feasible to run the application with L-threads. If the legacy code modifies the default behavior using attributes then if may be necessary to make some adjustments to eliminate those requirements. Blocking system API calls

It is important to understand what other system services the application may be using, bearing in mind that in a cooperatively scheduled environment a thread cannot block without stalling the scheduler and with it all other cooperative threads. Any kind of blocking system call, for example file or socket IO, is a potential problem, a good tool to analyze the application for this purpose is the strace utility.

There are many strategies to resolve these kind of issues, each with it merits. Possible solutions include:

  • Adopting a polled mode of the system API concerned (if available).
  • Arranging for another core to perform the function and synchronizing with that core via constructs that will not block the L-thread.
  • Affinitizing the thread to another scheduler devoted (as a matter of policy) to handling threads wishing to make blocking calls, and then back again when finished. Locks and spinlocks

Locks and spinlocks are another source of blocking behavior that for the same reasons as system calls will need to be addressed.

If the application design ensures that the contending L-threads will always run on the same scheduler then it its probably safe to remove locks and spin locks completely.

The only exception to the above rule is if for some reason the code performs any kind of context switch whilst holding the lock (e.g. yield, sleep, or block on a different lock, or on a condition variable). This will need to determined before deciding to eliminate a lock.

If a lock cannot be eliminated then an L-thread mutex can be substituted for either kind of lock.

An L-thread blocking on an L-thread mutex will be suspended and will cause another ready L-thread to be resumed, thus not blocking the scheduler. When default behavior is required, it can be used as a direct replacement for a pthread mutex lock.

Spin locks are typically used when lock contention is likely to be rare and where the period during which the lock may be held is relatively short. When the contending L-threads are running on the same scheduler then an L-thread blocking on a spin lock will enter an infinite loop stopping the scheduler completely (see Infinite loops below).

If the application design ensures that contending L-threads will always run on different schedulers then it might be reasonable to leave a short spin lock that rarely experiences contention in place.

If after all considerations it appears that a spin lock can neither be eliminated completely, replaced with an L-thread mutex, or left in place as is, then an alternative is to loop on a flag, with a call to lthread_yield() inside the loop (n.b. if the contending L-threads might ever run on different schedulers the flag will need to be manipulated atomically).

Spinning and yielding is the least preferred solution since it introduces ready queue backlog (see also Ready queue backlog). Sleeps and delays

Yet another kind of blocking behavior (albeit momentary) are delay functions like sleep(), usleep(), nanosleep() etc. All will have the consequence of stalling the L-thread scheduler and unless the delay is very short (e.g. a very short nanosleep) calls to these functions will need to be eliminated.

The simplest mitigation strategy is to use the L-thread sleep API functions, of which two variants exist, lthread_sleep() and lthread_sleep_clks(). These functions start an rte_timer against the L-thread, suspend the L-thread and cause another ready L-thread to be resumed. The suspended L-thread is resumed when the rte_timer matures. Infinite loops

Some applications have threads with loops that contain no inherent rescheduling opportunity, and rely solely on the OS time slicing to share the CPU. In a cooperative environment this will stop everything dead. These kind of loops are not hard to identify, in a debug session you will find the debugger is always stopping in the same loop.

The simplest solution to this kind of problem is to insert an explicit lthread_yield() or lthread_sleep() into the loop. Another solution might be to include the function performed by the loop into the execution path of some other loop that does in fact yield, if this is possible. Thread local storage

If the application uses thread local storage, the use case should be studied carefully.

In a legacy pthread application either or both the __thread prefix, or the pthread set/get specific APIs may have been used to define storage local to a pthread.

In some applications it may be a reasonable assumption that the data could or in fact most likely should be placed in L-thread local storage.

If the application (like many DPDK applications) has assumed a certain relationship between a pthread and the CPU to which it is affinitized, there is a risk that thread local storage may have been used to save some data items that are correctly logically associated with the CPU, and others items which relate to application context for the thread. Only a good understanding of the application will reveal such cases.

If the application requires an that an L-thread is to be able to move between schedulers then care should be taken to separate these kinds of data, into per lcore, and per L-thread storage. In this way a migrating thread will bring with it the local data it needs, and pick up the new logical core specific values from pthread local storage at its new home.

40.5.4. Pthread shim

A convenient way to get something working with legacy code can be to use a shim that adapts pthread API calls to the corresponding L-thread ones. This approach will not mitigate any of the porting considerations mentioned in the previous sections, but it will reduce the amount of code churn that would otherwise been involved. It is a reasonable approach to evaluate L-threads, before investing effort in porting to the native L-thread APIs. Overview

The L-thread subsystem includes an example pthread shim. This is a partial implementation but does contain the API stubs needed to get basic applications running. There is a simple “hello world” application that demonstrates the use of the pthread shim.

A subtlety of working with a shim is that the application will still need to make use of the genuine pthread library functions, at the very least in order to create the EAL threads in which the L-thread schedulers will run. This is the case with DPDK initialization, and exit.

To deal with the initialization and shutdown scenarios, the shim is capable of switching on or off its adaptor functionality, an application can control this behavior by the calling the function pt_override_set(). The default state is disabled.

The pthread shim uses the dynamic linker loader and saves the loaded addresses of the genuine pthread API functions in an internal table, when the shim functionality is enabled it performs the adaptor function, when disabled it invokes the genuine pthread function.

The function pthread_exit() has additional special handling. The standard system header file pthread.h declares pthread_exit() with __attribute__((noreturn)) this is an optimization that is possible because the pthread is terminating and this enables the compiler to omit the normal handling of stack and protection of registers since the function is not expected to return, and in fact the thread is being destroyed. These optimizations are applied in both the callee and the caller of the pthread_exit() function.

In our cooperative scheduling environment this behavior is inadmissible. The pthread is the L-thread scheduler thread, and, although an L-thread is terminating, there must be a return to the scheduler in order that the system can continue to run. Further, returning from a function with attribute noreturn is invalid and may result in undefined behavior.

The solution is to redefine the pthread_exit function with a macro, causing it to be mapped to a stub function in the shim that does not have the noreturn attribute. This macro is defined in the file pthread_shim.h. The stub function is otherwise no different than any of the other stub functions in the shim, and will switch between the real pthread_exit() function or the lthread_exit() function as required. The only difference is that the mapping to the stub by macro substitution.

A consequence of this is that the file pthread_shim.h must be included in legacy code wishing to make use of the shim. It also means that dynamic linkage of a pre-compiled binary that did not include pthread_shim.h is not be supported.

Given the requirements for porting legacy code outlined in Porting legacy code to run on L-threads most applications will require at least some minimal adjustment and recompilation to run on L-threads so pre-compiled binaries are unlikely to be met in practice.

In summary the shim approach adds some overhead but can be a useful tool to help establish the feasibility of a code reuse project. It is also a fairly straightforward task to extend the shim if necessary.

Note: Bearing in mind the preceding discussions about the impact of making blocking calls then switching the shim in and out on the fly to invoke any pthread API this might block is something that should typically be avoided. Building and running the pthread shim

The shim example application is located in the sample application in the performance-thread folder

To build and run the pthread shim example

  1. Go to the example applications folder

    export RTE_SDK=/path/to/rte_sdk
    cd ${RTE_SDK}/examples/performance-thread/pthread_shim
  2. Set the target (a default target is used if not specified). For example:

    export RTE_TARGET=x86_64-native-linuxapp-gcc

    See the DPDK Getting Started Guide for possible RTE_TARGET values.

  3. Build the application:

  4. To run the pthread_shim example

    lthread-pthread-shim -c core_mask -n number_of_channels

40.5.5. L-thread Diagnostics

When debugging you must take account of the fact that the L-threads are run in a single pthread. The current scheduler is defined by RTE_PER_LCORE(this_sched), and the current lthread is stored at RTE_PER_LCORE(this_sched)->current_lthread. Thus on a breakpoint in a GDB session the current lthread can be obtained by displaying the pthread local variable per_lcore_this_sched->current_lthread.

Another useful diagnostic feature is the possibility to trace significant events in the life of an L-thread, this feature is enabled by changing the value of LTHREAD_DIAG from 0 to 1 in the file lthread_diag_api.h.

Tracing of events can be individually masked, and the mask may be programmed at run time. An unmasked event results in a callback that provides information about the event. The default callback simply prints trace information. The default mask is 0 (all events off) the mask can be modified by calling the function lthread_diagniostic_set_mask().

It is possible register a user callback function to implement more sophisticated diagnostic functions. Object creation events (lthread, mutex, and condition variable) accept, and store in the created object, a user supplied reference value returned by the callback function.

The lthread reference value is passed back in all subsequent event callbacks, the mutex and APIs are provided to retrieve the reference value from mutexes and condition variables. This enables a user to monitor, count, or filter for specific events, on specific objects, for example to monitor for a specific thread signaling a specific condition variable, or to monitor on all timer events, the possibilities and combinations are endless.

The callback function can be set by calling the function lthread_diagnostic_enable() supplying a callback function pointer and an event mask.

Setting LTHREAD_DIAG also enables counting of statistics about cache and queue usage, and these statistics can be displayed by calling the function lthread_diag_stats_display(). This function also performs a consistency check on the caches and queues. The function should only be called from the master EAL thread after all slave threads have stopped and returned to the C main program, otherwise the consistency check will fail.