Profiling HIP Code

This section describes the profiling and debugging capabilities that HIP provides. Profiling information can viewed in the CodeXL visualization tool or printed directly to stderr as the application runs. This document starts with some of the general capabilities of CodeXL and then describes some of the additional HIP marker and debug features.

CodeXL Profiling

Collecting and Viewing Traces

Using rocm-profiler timestamp profiling

rocm-profiler is a command-line tool for tracing any application that uses ROCr API, including HCC and HIP. rocm-profiler’s timeline trace will show the beginning and end for all kernel commands, data transfer commands, and HSA Runtime (ROCr) API calls. The trace results are saved into a file, which by convention uses the “atp” extension. Here is an example that shows how to run the command-line profiler:

$ /opt/rocm/bin/rocm-profiler -o <outputATPFileName> -A -T  <applicationName> <applicationArguments>

Using rocm-profiler performance counter collection

rocm-profiler can record performance counter information to provide greater insight inside a kernel, such as the memory bandwidth, ALU busy percentage, and cache statistics. Collecting the common set of useful counters requires passing the counter configuration files for two passes:

$ /opt/rocm/bin/rocm-profiler -C -O --counterfile /opt/rocm/profiler/counterfiles/counters_HSA_Fiji_pass1 --counterfile /opt/rocm/profiler/counterfiles/counters_HSA_Fiji_pass2  <applicationName> <applicationArguments>

Using CodeXL to view profiling results

The trace can be loaded and viewed in the CodeXL visualization tool:

  • Open the CodeXL GUI, create an new project, and switch to “Profile Mode”:

  • $ CodeXL &

  • [File->New Project, leave fields as is, just click “OK”]

  • [Profile->Switch to Profile Mode]

  • Load timestamp tracing results into a timeline view:

  • Right click on the project in the CodeXL Explorer view

  • Click “Import Session…”

  • Select to $HOME/apitrace.atp (or appropriate .atp file if you used another file name)

  • Load the performance counter results

  • Right click on the project in the CodeXL Explorer view

  • Click “Import Session…”

  • Select $HOME/Session1.csv (or appropriate .csv file if you used another file name)

More information on CodeXL

rocm-profiler –help will show additional options and usage guidelines.

See this blog for more information on profiling ROCm apps (including HIP) with CodeXL.

The 2.2 version of Windows CodeXL does not correctly handle Linux line-endings. If you are collecting a trace on Linux and then viewing it with the 2.2 Windows CodeXL, first convert the line ending in the .atp file to Windows-style line endings.

HIP Markers

Profiling HIP APIs

HIP can generate markers at function beginning and end which are displayed on the CodeXL timeline view. HIP 1.0 compiles marker support by default, and you can enable it by setting the HIP_PROFILE_API environment variable and then running the rocm-profiler:

# Use profile to generate timeline view:
export HIP_PROFILE_API=1
$ /opt/rocm/bin/rocm-profiler -A -T <applicationName> <applicationArguments>

Or
$ /opt/rocm/bin/rocm-profiler -e HIP_PROFILE_API=1 -A -T <applicationName> <applicationArguments>

HIP_PROFILE_API supports two levels of information.

  • HIP_PROFILE_API=1 : Short format. Print name of API but no arguments. For example: hipMemcpy

  • HIP_PROFILE_API=2 : Long format. Print name of API + values of all function arguments. For example: hipMemcpy (0x7f32154db010, 0x50446e000, 4000000, hipMemcpyDeviceToHost)

Adding markers to applications

Markers can be used to define application-specific events that will be recorded in the ATP file and displayed in the CodeXL GUI. This can be particularly useful for visualizing how the higher-level phases of application behavior relate to the lower level HIP APIs, kernel launches, and data transfers. For example, an instrumented machine learning framework could show the beginning and ending of each layer in the network.

Markers have a specific begin and end time, and can be nested. Nested calls are displayed hierarchically in the CodeXL GUI, with each level of the hierarchy occupying a different row.

The HIP APis are defined in “hip_profile.h”:

#include <hip/hip_profile.h>

HIP_BEGIN_MARKER(const char *markerName, const char *groupName);
HIP_END_MARKER();

HIP_BEGIN_MARKER("Setup", "MyAppGroup");
// ...
// application code for setup
// ...
HIP_END_MARKER();

For C++ codes, HIP also provides a scoped marker which records the start time when constructed and the end time when the scoped marker is destructed at the end of the scope. This provides a convenient, single-line mechanism to record an event that neatly corresponds to a region of code.

void FunctionFoo(...)
{
  HIP_SCOPED_MARKER("FunctionFoo", "MyAppGroup"); // Marker starts recording here.

  // ...
  // Function implementation
  // ...

  // Marker destroyed here and records end time stamp.
};

The HIP marker API is only supported on ROCm platform. The marker macros are defined on CUDA platforms and will compile, but are silently ignored at runtime.

This HIP sample shows the profiler marker API used in a small application.

More information on the marker API can be found in the profiler header file and PDF in a ROCm installation:

  • /opt/rocm/profiler/CXLActivityLogger/include/CXLActivityLogger.h

  • /opt/rocm/profiler/CXLActivityLogger/doc/CXLActivityLogger.pdf

Additional HIP Profiling Features

Demangling C++ Kernel Names

HIP includes the hipdemangleatp tool which can post-process an ATP file to “demangle” C++ names. Mangled kernel names encode the C++ arguments and other information, and are guaranteed to be unique even for cases such as operator overloading. However, the mangled names can be quite verbose. For example:

ZZ39gemm_NoTransA_MICRO_NBK_M_N_K_TS16XMTS4RN2hc16accelerator_viewEPKflS3_lPfliiiiiiffEN3_EC__719__cxxamp_trampolineElililiiiiiiS3_iS3_S4_ff

hipdemangleatp will convert this into the more readable:

gemm_NoTransA_MICRO_NBK_M_N_K_TS16XMTS4

The hipdemangleatp tool operates on the ATP file “in-place” and thus replaces the input file with the demangled version.

$ hipdemangleatp myfile.atp

The kernel name is also shown in some of the summary htlm files (Top10 kernels). These can be regenerated from the demangled ATP file by re-running rocm-profiler:

$ rocm-profiler -T --atpfile myfile.atp

A future version of CodeXL may directly integrate demangle functionality.

Controlling when profiling starts and ends

hipProfilerStart() and hipProfilerEnd() can be inserted into an application to control which phases of the applications are profiled. These APIs can be used to skip initialization code or to focus profiling on a desired region, and are particularly useful for large long-running applications. See the API documentation for more information. These APIs work on both ROCm and CUDA paths.

On ROCm, the following environment variables can be used to control when profiling occurs:

HIP_DB_START_API  : Comma-separated list of tid.api_seq_num for when to start debug and profiling.
HIP_DB_STOP_API   : Comma-separated list of tid.api_seq_num for when to stop debug and profiling.

HIP/ROCm assigns a monotonically increasing sequence number to the APIs called from each thread. The thread and API sequence number can be used in the above API to control when tracing starts and stops. These flags also control the HIP_DB messages (described below).

When using these options, start the profiler with profiling disabled:

# ROCm:
$ rocm-profiler --startdisabled ...
# CUDA:
$ nvprof --profile-from-start-off ...

This feature is under development.

Reducing timeline trace output file size

If the application is already recording the HIP APIs, the HSA APIs are somewhat redundant and the ATP file size can be substantially reduced by not recording these APIs. HIP includes a text file that lists all of the HSA APIs and can assist in this filtering:

$ rocm-profiler -F hip/bin/hsa-api-filter-cxl.txt

This file can be copied and edited to provide more selective HSA event recording.

How to enable profiling at HIP build time

Recent pre-built packages of HIP are always built with profiling support enabled. For developer builds, you must enable marker support manually when compiling HIP.

  1. Build HIP with ATP markers enabled HIP pre-built packages are enabled with ATP marker support by default. To enable ATP marker support when building HIP from source, use the option -DCOMPILE_HIP_ATP_MARKER=1 during the cmake configure step. Build and install HIP.

    $ mkdir build && cd build
    $ cmake .. -DCOMPILE_HIP_ATP_MARKER
    $ make install
    
  2. Install ROCm-Profiler Installing HIP from the rocm pre-built packages, installs the ROCm-Profiler as well. Alternatively, you can build ROCm-Profiler using the instructions here.

  3. Recompile the target application

Then follow the steps above to collect a marker-enabled trace.

Tracing and Debug

Tracing HIP APIs

The HIP runtime can print the HIP function strings to stderr using HIP_TRACE_API environment variable. The trace prints two messages for each API - one at the beginning of the API call (line starts with “<<”) and one at the end of the API call (line ends with “>>”). Here’s an example for one API followed by a description for the sections of the trace:

<<hip-api tid:1.6 hipMemcpy (0x7f32154db010, 0x50446e000, 4000000, hipMemcpyDeviceToHost)
  hip-api tid:1.6 hipMemcpy                      ret= 0 (hipSuccess)>>
  • <<hip-api is the header used for all HIP API debug messages. The message is also shown in a specific color. This can be used to distinguish this API from other HIP or application messages.

  • tid:1.6 indicates that this API call came from thread #1 and is the 6th API call in that thread. When the first API in a new thread is called, HIP will associates a short sequential ID with that thread. You can see the full thread ID (reported by C++) as 0x7f6183b097c0 in the example below.

  • hipMemcpy is the name of the API.

  • The first line then prints a comma-separated list of the arguments to the function. APIs which return values to the caller by writing to pointers will show the pointer addresses rather than the pointer contents. This behavior may change in the future.

  • The second line shows the completion of the API, including the numeric return value (ret= 0) as well as an string representation for the error code (hipSuccess). If the returned error code is non-zero, then the csecond line message is shown in red (unless HIP_TRACE_API_COLOR is “none” - see below).

Heres a specific example showing the output of the square program running on HIP:

$ HIP_TRACE_API=1  ./square.hip.out
  hip-api tid:1:HIP initialized short_tid#1 (maps to full_tid: 0x7f6183b097c0)
<<hip-api tid:1.1 hipGetDeviceProperties (0x7ffddb673e08, 0)
  hip-api tid:1.1 hipGetDeviceProperties         ret= 0 (hipSuccess)>>
info: running on device gfx803
info: allocate host mem (  7.63 MB)
info: allocate device mem (  7.63 MB)
<<hip-api tid:1.2 hipMalloc (0x7ffddb673fb8, 4000000)
  hip-api tid:1.2 hipMalloc                      ret= 0 (hipSuccess)>>
<<hip-api tid:1.3 hipMalloc (0x7ffddb673fb0, 4000000)
  hip-api tid:1.3 hipMalloc                      ret= 0 (hipSuccess)>>
info: copy Host2Device
<<hip-api tid:1.4 hipMemcpy (0x50409d000, 0x7f32158ac010, 4000000, hipMemcpyHostToDevice)
  hip-api tid:1.4 hipMemcpy                      ret= 0 (hipSuccess)>>
info: launch 'vector_square' kernel
1.5 hipLaunchKernelGGL 'HIP_KERNEL_NAME(vector_square)' gridDim:{512,1,1} groupDim:{256,1,1} sharedMem:+0 stream#0.0
info: copy Device2Host
<<hip-api tid:1.6 hipMemcpy (0x7f32154db010, 0x50446e000, 4000000, hipMemcpyDeviceToHost)
  hip-api tid:1.6 hipMemcpy                      ret= 0 (hipSuccess)>>
info: check result
PASSED!

HIP_TRACE_API supports multiple levels of debug information:

  • 0x1 = print all HIP APIs. This is the most verbose setting; the flags below allow selecting a subset.

  • 0x2 = print HIP APIs which initiate GPU kernel commands. Includes hipLaunchKernelGGL, hipLaunchModuleKernel

  • 0x4 = print HIP APIs which initiate GPU memory commands. Includes hipMemcpy*, hipMemset*.

  • 0x8 = print HIP APIs which allocate or free memory. Includes hipMalloc, hipHostMalloc, hipFree, hipHostFree.

These can be combined. For example, HIP_TRACE_API=6 shows a concise view of the HIP commands (both kernel and memory) that are sent to the GPU.

Color

Note this trace mode uses colors. “less -r” can handle raw control characters and will display the debug output in proper colors. You can change the color used for the trace mode with the HIP_TRACE_API_COLOR environment variable. Possible values are None/Red/Green/Yellow/Blue/Magenta/Cyan/White. None will disable use of color control codes for both the opening and closing and may be useful when saving the trace file or when a pure text trace is desired.