TornadoVM Profiler

The TornadoVM profiler can be enabled either from the command line (via a flag from the tornado command), or via an ExecutionPlan in the source code.

1. Enable the Profiler from the Command Line

To enable the TornadoVM profiler, developers can use --enableProfiler <silent|console>.

  • console: It prints a JSON entry for each task-graph executed via STDOUT.

  • silent : It enables profiling information in silent mode. Use the profiler API to query the values.


$ tornado --enableProfiler console  -m tornado.examples/ --params="100000"
    "s0": {
        "TOTAL_BYTE_CODE_GENERATION": "10465146",
        "COPY_OUT_TIME": "24153",
        "COPY_IN_TIME": "72044",
        "TOTAL_DRIVER_COMPILE_TIME": "63298322",
        "TOTAL_CODE_GENERATION_TIME": "16564279",
        "TOTAL_TASK_GRAPH_TIME": "285317518",
        "TOTAL_GRAAL_COMPILE_TIME": "109520628",
        "TOTAL_KERNEL_TIME": "47974",
        "TOTAL_COPY_OUT_SIZE_BYTES": "400024",
        "TOTAL_COPY_IN_SIZE_BYTES": "1600096",
        "s0.t0": {
            "BACKEND": "SPIRV",
            "METHOD": "VectorAddInt.vectorAdd",
            "DEVICE_ID": "0:0",
            "DEVICE": "Intel(R) UHD Graphics [0x9bc4]",
            "TASK_COMPILE_GRAAL_TIME": "109520628",
            "TASK_CODE_GENERATION_TIME": "16564279",
            "TASK_COMPILE_DRIVER_TIME": "63298322",
            "TASK_KERNEL_TIME": "47974"

All timers are printed in nanoseconds.

1. Enabling/Disabling the Profiler using the TornadoExecutionPlan

The profiler can be enable/disable using the TornadoExecutionPlan API:

// Enable the profiler and print report in STDOUT
executionPlan.withProfiler(ProfilerMode.CONSOLE) //
    .withDevice(device) //

It is also possible to enable the profiler without live reporting in STDOUT and query the profiler after the execution:

// Enable the profiler in silent mode
executionPlan.withProfiler(ProfilerMode.SILENT) //
    .withDevice(device) //

TornadoExecutionResult executionResult = executorPlan.execute();
TornadoProfilerResult profilerResult = executionResult.getProfilerResult();

// Print Kernel Time
System.out.println(profilerResult.getDeviceKernelTime() + " (ns)");

Explanation of all values

  • COPY_IN_TIME: OpenCL timers for copy in (host to device)

  • COPY_OUT_TIME: OpenCL timers for copy out (device to host)

  • DISPATCH_TIME: time spent for dispatching a submitted OpenCL command

  • TOTAL_KERNEL_TIME: It is the sum of all OpenCL kernel timers. For example, if a task-graph contains 2 tasks, this timer reports the sum of execution of the two kernels.

  • TOTAL_BYTE_CODE_GENERATION: time spent in the Tornado bytecode generation.

  • TOTAL_TASK_GRAPH_TIME: Total execution time. It contains all timers.

  • TOTAL_GRAAL_COMPILE_TIME: Total compilation with Graal (from Java. to OpenCL C / PTX)

  • TOTAL_DRIVER_COMPILE_TIME: Total compilation with the driver (once the OpenCL C / PTX code is generated, the time that the driver takes to generate the final binary).

  • TOTAL_CODE_GENERATION_TIME: Total code generation time. This value represents the elapsed time from the last Graal compilation phase in the LIR to the target backend code (e.g., OpenCL, PTX or SPIR-V).

Then, for each task within a task-graph, there are usually three timers, one device identifier and two data transfer metrics:

  • BACKEND: TornadoVM backend selected for the method execution on the target device. It could be either SPIRV, PTX or OpenCL.

  • DEVICE_ID: platform and device ID index.

  • DEVICE: device name as provided by the OpenCL driver.

  • TASK_COPY_IN_SIZE_BYTES: size in bytes of total bytes copied-in for a given task.

  • TASK_COPY_OUT_SIZE_BYTES: size in bytes of total bytes copied-out for a given task.

  • TASK_COMPILE_GRAAL_TIME: time that takes to compile a given task with Graal.

  • TASK_COMPILE_DRIVER_TIME: time that takes to compile a given task with the OpenCL/CUDA driver.

  • TASK_KERNEL_TIME: kernel execution for the given task (Java method).

  • TASK_CODE_GENERATION_TIME: time that takes the code generation from the LIR to the target backend code (e.g., SPIR-V).


When the task-graph is executed multiple times (through an execution plan), timers related to compilation will not appear in the Json time-report. This is because the generated binary is cached and there is no compilation after the second iteration.

Save profiler into a file

Use the option --dumpProfiler <FILENAME> to store the profiler output in a JSON file.

Parsing Json files

TornadoVM creates the profiler-app.json file with multiple entries for the application (one per task-graph invocation).

TornadoVM’s distribution includes a set of utilities for parsing and obtaining statistics:

$ profiler-app.json output.json
$ output.json

['', 'output.json']
Processing file: output.json
Num entries = 10
    TaskName, s0.t0

MEDIANS    ### Print median values for each timer

Code feature extraction for the OpenCL/PTX generated code

To enable TornadoVM’s code feature extraction, use the following flag: -Dtornado.feature.extraction=True.


$ tornado --jvm="-Dtornado.feature.extraction=True" -m tornado.examples/ --params "1024 1"
    "nBody": {
        "BACKEND" : "PTX",
        "DEVICE_ID": "0:2",
        "DEVICE": "GeForce GTX 1650",
        "Global Memory Loads":  "15",
        "Global Memory Stores":  "6",
        "Constant Memory Loads":  "0",
        "Constant Memory Stores":  "0",
        "Local Memory Loads":  "0",
        "Local Memory Stores":  "0",
        "Private Memory Loads":  "20",
        "Private Memory Stores":  "20",
        "Total Loops":  "2",
        "Parallel Loops":  "1",
        "If Statements":  "2",
        "Integer Comparison":  "2",
        "Float Comparison":  "0",
        "Switch Statements":  "0",
        "Switch Cases":  "0",
        "Vector Operations":  "0",
        "Integer & Float Operations":  "57",
        "Boolean Operations":  "9",
        "Cast Operations":  "2",
        "Float Math Functions":  "1",
        "Integer Math Functions":  "0"

Use the option -Dtornado.feature.extraction=True -Dtornado.features.dump.dir=FILENAME. FILENAME can contain the filename and the full path (e.g. features.json).

TornadoVM allows redirecting profiling and feature extraction logs to a specific port. This feature can be enabled with the option
The following example redirects the profiler output to the localhost ( and to a specified open port (2000):
$ tornado --jvm="-Dtornado.profiler=True" -m tornado.examples/ --params "100000"

To test that the socket streams the logs correctly, open a local server in a different terminal with the following command:

$ ncat -k -l 2000