Afanasy is represented by a special multi-functional ROP. You can connect several other ROP-s to Afanasy ROP to render. You can connect several Afanasy ROP-s to Afanasy ROP for a job with a complex dependencies.
- Generate a job and send it to server.
- Start Paused
- Send a job in off-line state.
- Preview Approval
- Set job preview approval flag. For example, if sequential is 10, it will render every 10 frame and wait for approve.
- Job Name
Afanasy job name.
- Output Driver
You can not (don’t want) to connect Afanasy ROP to render ROP, you can specify it.
- Valid Frame Range:
- Render Any Frame
- Use frame range form downstream node. Or render current frame if no range in network defined.
- Render Frame Range
- Render this specified frame range.
- Render Frame Range Only (Strict)
- Render this specified frame range. Other ROP-s will wait this whole frame range rendered.
- Single Task
- Generate single task for whole frame range, useful for simulations.
- Local Render
Render on the local render client. Job host mask will be automatically set to the local host name.
- Frames Per Task
Number of frames in each task.
1 Render frames one by one from the first to the last 10 Render every 10 frame at first, than render last other frames -1 Render frames backwards from the last to the first -10 Render every 10 frame at first backwards, than render last other frames backwards 0 Render the first, the last, the middle, the middle of the middle and so on
- Wait Time
Set job time_wait parameter to the current day Hours and Minutes. If current time will be greater than specified, the next day will be used.
- Render With Take
Specify take to render.
- Connected Nodes Are Independent
Allow run the same frames of all connected nodes at the same time.
- Allow Sub-Task Dependence
Tasks can wait other tasks to be done partially. Useful for simulations. Frames render can start w/o waiting the whole simulation is finished.
- Ignore ROP Inputs
Do not execute input ROP-s.
- OS type the job can launch tasks on:
- Any: any OS.
- Native: the same as this OTL was launched on.
- Use tickets:
- Auto: Submission script will try to set tickets automatically, depending on the ROP to render.
- Memory: If not zero, this amount of MEM tickets will be set.
- Aux: Any other tickets string as
TICKET:COUNTcomma separated list.
- Use pools that are specified as
pool:prioritycomma separated list.
- Enable Extended Parameters
- To switch ON/OFF it fast.
- Job Branch
$HIPshould be used in most cases. No matter how deep you placed hip file in file-system. It just help to find server an existing parent branch (department, project, scene).
- Hosts Mask
- Hosts names pattern where job can run on (empty value means that job can run on host with any name).
- Hosts Mask Exclude: Hosts names pattern where job can not to run on.
- Depend Mask
- Same user jobs names pattern to wait to be done to start
- Depend Mask Global: Same as Depend Mask, but waits for a jobs from any user.
- Job order in user jobs list
-1means to use default value).
- Maximum Running Tasks
- Maximum tasks job can run at the same time
-1means no limit).
- Per Host
- Maximum Running Tasks Per Host: Maximum running tasks on the same host.
-1means no limit).
- Tasks capacity value (
-1means use default value). Render must have enough free capacity to run it.
- Render Time Min
- Minimum time task should run (seconds). Sometimes tasks finishes with a good exit status too early.
- Task maximum running time (in hours). If task will not finish after this time, it will considered as an error and will be restarted.
- Progress Timeout
- If a task will not produce any output for this time (in hours), it will be considered as an error.
- Min RAM
- Minimum free memory (Gigabytes) should have render client to be able to start a task.
- Override Service
- This will be any custom service name for a job block tasks.
- Override Parser: This will be any custom parser name for a job block tasks.
- Life Time
- DONE job will be automatically deleted after this time (in hours). Useful for some auxiliary jobs.
- Files Check
- Service (task instanced Python class) can check rendered files for existence.
Submitter (script) should know file names that task should produce.
Can not work on expressions/takes/overrides.
- Skip Existing
- Render can check files for existence before run task command.
- It is key-value dictionary. Key used as an environment variable name. This environment variables will be added to task process environment.
- Get Houdini Environment
- Get and store in variables Houdini location and version. It can be used in setup scripts to launch the same version, initialize proper plug-ins.
- Remove Houdini Environment
- Remove Houdini related variables (starting with “HOUDINI_”).
- Clear Environment
- Remove all variables.
- Controls Node
Distributed simulation control node.
- Number Of Slices
Distributed simulation slices number.
Distributed simulation slices tasks should communicate via tracker service.
- Tracker task capacity.
- Host Mask
- Tracker will run only hosts that names match this regular expression.
- Tracker task service.
- Tracker task parser.
- Manual Tracker
- Use manual launched tracker service at specified Address and Port
Separate Render allows to separate render process on IFD files generation and render it by
It can give several advantages on some heavy scenes.
Separate render generates a job that can:
- Render images locally in temporary folder and copy whole image after successful render. It can save your network traffic as render do not send small portions of an image during render process.
- Generate IFD file locally and then render it in separate process but in the same task. It can save render memory.
- Split one frame on tiles to render them simultaneously. So you can increase speed of one frame render. And also it can reduce memory needed to render a frame.
- Cleanup rendered IFD files and joined tiles images.
- Enable Separate Render
- Turn this feature on.
- Run ROP
- Run ROP to generate files to render. Houdini will generate IFD files for mantra.
- Join Render Stages
- Generate IFD files and render in the same task. In this case IFD files will be generated to local temporary folder. It can save and memory usage and network traffic.
- Read Parameters from ROP
- Read files to generate and images to render parameters from specified ROP.
- Render Arguments
- Arguments for render command. Usually files and may be some other options.
- Files to generate.
- Delete ROP Files On Job Deletion
- ROP files (IFD-s) can be deleted when user will delete the job.
- Images which render will produce. Needed for tile render, AfWatch preview/thumbnails.
- Tile Render
- Enable rendering tiles and then combine them.
- Tiles divisions.
Run any custom command.
For example you can render IFD files using
generate a preview movie with
- Custom Command Mode
- Add custom command tasks block to a job.
- Tasks block name. If empty the first word of the command will be used.
- The command.
- Prefix with $AF_CMD_PREFIX
$AF_CMD_PREFIXenvironment variable value to the beginning of the command. This may be needed for some software (environment) setup.
- Some files you can point to use in command.
- Delete Files On Job Deletion
- Delete this files when user will delete job.
- Specify result picture here to enable tasks preview.
- Tasks block service. If empty the first word of the command will be used.
- Tasks block parser.
This can be used to explain other ROP network what to do with Afanasy node.
- Afanasy ROP
- Specify Afanasy ROP to execute by SOHO.
- Script that will be executed on SOHO demand. That default script will execute Submit button on a specified Afanasy ROP.
afanasy ROP to your render ROP.
The job consists of single tasks block. Each task represents a frame or several number of frames, specified in Frames Per Task parameter.
You can send any custom command to your farm.
Usually you need separate IFD files generation and run
mantra as a standalone process to render.
This job consists of two blocks of tasks.
The first block produced by
mantra_ifd node, with
Disk File parameter turned on.
Next block runs
files parameter pointing to the generated files.
You can split single image to render on several hosts. Each host (task) will produce a tile - some part of an image. Tiles will be combined in a single image.
Tile job consists of three blocks:
- Generate IFD files.
- Render tiles with
- Join tiles to assemble an image. If tiles were successfully joined they will be removed. At the end of this stage, IFD will be removed, if it was asked.
itilestitch tool is used to join tiles.
Sub Task Dependence¶
This option is designed to start to render simulation without waiting the whole simulation is finished.
The first block of a job is a simulation. It consists of a single task (Frames Per Task parameter is set to the whole frame range). The second block set to wait the first one with sub-task dependence. So it begins to render as first frames of a simulation completed, while the simulation task is still running.
We also can notice here, that the render block got HYTHON and MANTRA tickets, while the simulation block got only HYTHON ticket
You can construct a complex Afanasy ROP network to construct a complex job.
This job consists of a simulation with sub-task dependence. Two caches waiting the simulation, but can run independently from each other. Mantra tile render which produces three blocks which wait all the cache. Two blocks for preview which can run independently but wait tile render tasks. One to convert EXR files to JPEG-s and one to generate a preview movie form EXR-s.
Houdini can calculate the same simulation on several machines.
How It Works¶
Simulation can be split on slices, so each machine calculates own slice. But different slices simulations should exchange information to pass data from slice to slice. Houdini has a special Python script simtracker.py for it. It needs to launch a server that simulations will connect to. So each slice simulation should know tracker address and port. Also tracker has a simple web interface to see logs.
What We Should Do¶
- Prepare distributed simulation, setup slices.
- Launch tracker server and get its address and port.
- Open several Houdini applications with simulation scene (on different machines or not).
- Specify tracker and port.
- Start each Houdini instance to simulate own slice.
- Stop tracker.
So, you can distribute Houdini simulation without any render farm manager.
Create a sphere.
Create simulation via Wispy Smoke shelf tool.
Apply Distribute Container shelf tool.
You will be moved to /out/ network.
Create Afanasy ROP node.
Set Output Driver to /obj/distribute_pyro/save_slices and in the Distributed Simulation tab set Controls Node to /obj/AutoDopNetwork/DISRIBUTE_pyro_CONTROLS. You can copy this values from HQueue Simulation ROP that was automatically created.
Uncheck Render Temporary HIP File option on Afanasy ROP. By default, Afanasy renders a temporary scene to allow user to continue working with original file. But in this case $HIPNAME variable will change, and it widely used in shelf tools and examples.
Go to /obj/AutoDopNetwork/.
Remove resize_container node.
- Disconnect distribute_pyro node from merge node (do not merge it with source). And connect it to the solver Velocity Update input.
Set slices divisions 1 x 2 x 1.
Now you can submit simulation by Afanasy ROP in /out/ network.
Afanasy will create a job that consists of four blocks each contains just one task. First block task to start tracker. A block (task) for each slice that waits tracker start. And the last block task to stop the tracker.
The first task block has a special service htracker. This service just adds job ID to the task command. Job ID is needed to manipulate job using JSON protocol. The command calls a special CGRU Python script
htracker --start --envblocks "save_slices.*|tracker-stop" --depblocks "save_slices.*"
- It starts Houdini simtracker in a separate thread and gets its address and port.
- Set other job blocks environment variables
TRACKER_PORTto blocks specified by –envblocks argument.
- Set slices job blocks depend masks to an empty string to blocks specified by –depblocks argument, So that blocks will wait nothing and can to start.
- Waits simtracker for completion.
The first slice simulation. Slices are simulated by CGRU multi-functional Hython script
cgru/plugins/houdini/hrendef_af.pythat Afanasy uses for almost everything.
hrender_af -s 1001 -e 1133 --by 1 -t "_current_" --ds_node "/obj/AutoDopNetwork/DISTRIBUTE_pyro_CONTROLS" --ds_address "localhost" --ds_port 8000 --ds_slice 0 "/opt/cgru/examples/houdini/distrib_pyro.hip" "/obj/distribute_pyro/save_slices"
Control node, tracker address and tracker port, that was specified in Afanasy ROP and passed by command line argument, will be overridden by environment variables.
Script will open HIP file, set control node tracker address and port parameters. Set SLICE variable to the specified slice number.
Run simulation ROP.
The second slice simulation. It is the same as the first, but with one key difference. Slice will be equal to 1.
hrender_af -s 1001 -e 1133 --by 1 -t "_current_" --ds_node "/obj/AutoDopNetwork/DISTRIBUTE_pyro_CONTROLS" --ds_address "localhost" --ds_port 8000 --ds_slice 1 "/opt/cgru/examples/houdini/distrib_pyro.hip" "/obj/distribute_pyro/save_slices"
Stop tracker. It will be performed by the same script that starts tracker.
It just sends
quitstring to tracker_address:tracker_port socket.
Afanasy TOP Scheduler¶
This node executes work items on farm using Afanasy render manager. It can schedule work items from TOP UI, and as standalone job. Using a standalone job you can close Houdini session and watch progress via Afanasy GUI.
Here is the scheduler nodes parameters description.
Almost anywhere in Afanasy
-1 means that the value is not set and defaults will be used.
- Job Name
- The name of the job where work items tasks will be appended to.
- Job Branch
- The branch of the job. The same value will be used if you submit graph as job.
- PDG Directory
- Specifies the directory where the cook generates intermediate files.
The intermediate files are placed in a subdirectory named
- Path Mapping
- If the PDG Path Map exists, then it is applied to file paths.
- Delocalizes paths using the PDG_DIR token.
- Path Map Zone
- When on, specifies a custom mapping zone to apply to all jobs executed by this scheduler.
Otherwise, the local platform is
Submit Graph As Job¶
- Submit Graph As Job
- Cooks the entire TOP network as a standalone job. Displays the status URI for the submitted job. The submitting Houdini session is detached from the cooking of the TOP network.
- Start Paused
- Start graph cooking job paused.
- Graph cooking job priority value.
- Cooking task capacity.
- Hosts Mask
- Hosts names regular expression, where graph job can run.
- Hosts names regular expression, where graph job can not run.
- Depend Mask
- Current user jobs names expression, that job will wait to start for.
- Any user jobs names expression, that job will wait to start for.
- Cooking job task block service name.
- Cooking job task block will need and take one ticket with this name. See tickets documentation for details.
You can override this parameters on each TOP node, except Job Priority which will be set to an entire job.
- Job Priority
- Priority value of a job were working items tasks will be executed.
- Work items tasks block capacity.
- Hosts Mask
- Hosts names regular expression, where tasks can run.
- Hosts names regular expression, where tasks can not run.
- Max Running Tasks
- Running tasks count at the same time limit.
- Per Host
- Running tasks count at the same time on the same host limit.
- Render Time Min (Sec)
- Minimum task running time limit. If task will finish for seconds below this value, task finish will be considered as with an error.
- Max (Hours)
- Maximum task running time limit. If task will run for hours above this value, it will be forced to stop with an error.
- Min RAM (GB)
- Host should have this count of Gigabytes of a free RAM to be able to run tasks.
- Tasks block service. If empty it will try to detect automatically. If node fetches ifd ROP, service will be hbatch_mantra, ffmpegencodevideo will be ffmpeg.
- asks block tickets. A comma separated list of key:count.
MEM:64,GPU:1. See tickets documentation for details.
- Automatically add common tickets. Almost all tasks launch hython, so HYTHON ticket will be added. If node fetches ifd ROP, MANTRA ticket will be added.
- Adds custom key-value environment variables to tasks block.
To override task parameter on TOP node add it via Edit Parameter Interface window:
- Report Item Fail On Error
If task gets error state, scheduler will report PDG that work item failed. You can turn it off and try to solve errors via Afanasy only. Read output for an error cause, try to fix it, restart task. And PDG will know nothing about it.
- Block On Failed Work Items
When this option is enabled the scheduler will block the cook from completing if there are any failed work items in that scheduler. This makes it possible to manually retry those work items, by preventing the PDG graph cook from ending before failed items can be retried. A cook that is blocked on failed work items can still be canceled using the ESC key, the cancel button in the TOP task bar, or the cancel API method.
- Validate Outputs When Recooking
When enabled, PDG will check the output files of work items when the graph recooks, to see if the files still exist on disk. Work items that are missing output files will be dirtied and cook again.
- Check Expected Outputs On Disk
When enabled, PDG will look on disk for any expected work items outputs that were not explicitly reported when the work item cooked. Expected outputs for a work item are checked immediately after the scheduler marks the work item as cooked. Output files that were reported by the work item normally while cooking will not be checked.
- Use IP Address
Use IP address instead of host name as work item result server address. Some times render farm can’t solve workstations by name. Also it can save DNS load.
Work item task can send progress to PDG itself. It is used by batch work item to notify that a specific frame (item in the batch) is done. This way PDG can start to render images when just first frames of a simulation rendered, and there is no need to wait the entire simulation finish. So work item should know address and port to send progress to.
- Tick Period
Sets the minimum time (in seconds) between calls to the onTick callback. This callback is called periodically when the graph is cooking. The callback is generally used to check the state of running work items.
Afanasy server heart beat is 1 second, so there is no sense to set this parameter less than a second.
- Max Items Per Tick
Sets the maximum number of ready item onSchedule callbacks between ticks.
For example by default the tick period is 1s and the max items per tick is 30. This means that scheduler can send a maximum of 30 work items per second to farm. Adjusting these values can be useful to control the load on the farm scheduler.
CGRU setup should be sourced before. To do this you can source setup.sh script in CGRU root folder. Afanasy Houdini operator library and Python module are located in:
You should add this folder
PYTHONPATH environment variables.
Houdini setup example (bash):
# Setup CGRU
# Setup CGRU houdini plugins location:
# Append HOUDINI_PATH with CGRU plugins:
# Append Python path with afanasy submission script:
If you avoid sourcing
cgru/setup.sh see Manual Environment Setup.