dispy version 4.8.3 has been released. In this version
ext_ip_addroption to dispynode.
recover_jobsfunction (which can be used for fault-recovery in case client crashes or loses network connection to nodes).
recover_jobsis now optional; if this option is not given, latest file with prefix
_dispy_is used (default falut-recovery files are of the form
dispy version 4.8.2 has been released. In this version,
dispy version 4.8.1 has been released. In this version crash with dispyscheduler (due to conflicts of names of variables and methods with change from asyncoro to pycos) has been fixed.
dispy version 4.8.0 has been released. In this release asyncoro module has been replaced with pycos module.
dispy version 4.7.7 has been released. This version fixes crash of dispyscheduler when starting.
dispy version 4.7.5 has been released. In this version
dispy version 4.7.4 has been released. In this version
dispy version 4.7.3 has been released. In this version
dispy version 4.7.2 has been released. In this version
dispy version 4.7.1 has been released. In this version
cleanup_nodesthat if set (to True), will cause dispynode to cleanup (i.e., remove any files transferred and generated by computations) even if computations set
cleanup=False. This can be used when nodes are being shared by multiple users and computations don't leave beind any files, which may take up disk space.
dispy version 4.7.0 has been released. In this version
cluster.submitno longer have args and kwargs attributes. These attributes used to store parameters used in job creation (i.e., parameters to
cluster.submit). When many jobs are created and not freed as soon as a job is finised, it is likely that the memory used to store such arguments may cause problems at the client / scheduler. Now these arguments are still stored in DispyJob instances, but are cleared by scheduler as soon as possible (e.g., when job is finished / terminated). If access to parameters used in job creation is necessary, then they can be maintained in client program using id attribute of job. In any case, when submitting large number of jobs, consider using
bounded_submit.pyto schedule only enough jobs to keep the processors busy and not all at once (which can cause memory issues).
dispy version 4.6.18 has been released. In this version
add_clusteretc. to use as coroutines instead of regular functions, as they use iterators shared with other coroutines. This prevents potential crashes when shared data structures are updated by other coroutines.
pip, asyncoro will be upgraded automatically; otherwise, please upgrade asyncoro.
dispy version 4.6.17 has been released. In this release
dispy version 4.6.16 has been released. In this release
--client_shutdownoption to dispynode. If this option is given, client program can call
dispynode_shutdown()in cleanup function to shutdown dispynode.
--save_configoption in dispynode now takes filename argument to save configuration in. In earlier releases
--configoption (which is used to load configuration) had to be specified to give the filename to save configuration.
dispy version 4.6.15 has been released. In this version
dispy version 4.6.14 has been released. In this version
dispy version 3.6.15 has been released. Following are changes since last release:
--max_file_size noption (to dispynode and dispyscheduler) to use n as maximum file size allowed.
dispy version 4.6.12 has been released. This release adds support for using psutil module to frequently gather and send node availability status information (availbe CPU as percent, memory in bytes and disk space in bytes) to cluster_status callback. This information is also shown in web browser (if httpd is used). The information is also sent to NodeAllocate's allocate method so clients can filter available nodes depending on computation's requirements.
dispy version 4.6.11 has been released. In this relase
dispy version 4.6.10 has been released. This release fixes initializing and closing nodes so a node is not initialized more than once (which then causes node not to respond to future computations due to a spurious computation still pending) and closing nodes is finished before client quits (otherwise the node may not be ready yet for new client if it starts quickly).
dispy version 4.6.9 has been released. In this version
dispyscheduler.py. If this option is given, or if client cluster is marked exclusive, the client(s) can update CPUs of node(s) (otherwise, clients won't be allowed to change CPUs, as this may prevent other clients to run their jobs). If node CPUs are changed by exclusive cluster and cooperative option is not used with dispyscheduler, the CPUs are reset to how they were before that cluster started. If CPUs are changed due to cooperative option, though, it is up to client clusters to cooperate and set/reset CPUs.
sys.moduleswhen they are done, so that previous computation's modules are not used by new computations (because they were cached in
dispy version 4.6.8 has been released. This version implements 3 scheduling algorithms for jobs in dispyscheduler (scheduler for SharedJobCluster):
dispy version 4.6.7 has been released. This version fixes initialization of SharedJobCluster client (broken in 4.6.6 release).
dispy version 4.6.6 has been released. Following is short summary of changes since last release: