# TDycore Development

This section contains topics that are useful to anyone developing the TDycore library or trying to use it in an application.

## Initializing the TDycore Library

Because the TDycore library uses MPI, PETSc, and other subsystems, we have defined a function to initialize these various subsystems at the beginning of any TDycore-based driver/program::

PetscErrorCode TDyInit(int argc, char *argv[]);


Call this function where you would ordinarily call MPI_Init or PetscInitialize. It has no effect on subsequent calls. You can check whether the library has been initialized with a call to:

PetscBool TDyInitialized(void);


Similarly, we have defined a finalization function to be called at the end of a TDycore-based program::

PetscErrorCode TDyFinalize(void);


Use this function instead of MPI_Finalize or PetscFinalize. This ensures that all TDycore subsystems properly free their resources.

## Memory Allocation and Deallocation

Within the TDycore library, the following functions are used to dynamically allocate and deallocate memory::

PetscErrorCode TDyAlloc(size_t size, void **result);
PetscErrorCode TDyRealloc(size_t size, void **memory);
PetscErrorCode TDyFree(void *memory);


TDyAlloc allocates and zero-initializes a contiguous block of memory of the specified size in bytes, aligned to PETSC_MEMALIGN. Use this function anywhere you would use malloc or any of the PETSc memory allocation functions like PetscMalloc, PetscCalloc, etc.

TDyRealloc resizes an existing block of memory to a new size. Call this where you would call realloc or PetscRealloc.

TDyFree frees an allocated block of memory. Call this where you would call free or PetscFree.

### Fortran 90 Interface

We offer two equivalent subroutines for Fortran 90, similar to their PETSc counterparts::

TDyInit(ierr)
TDyFinalize(ierr)


Both accept an integer that stores an error code if these subroutines encounter an issue.

## Timers and Profiling

We use PETSc’s Logging machinery <https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Profiling/index.html> to understand the performance of the dycores. In particular, we’ve provided some high-level wrappers around the PetscLogEvent <https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Profiling/PetscLogEvent.html> object that make it very easy to add timers for functions and blocks of code.

### The TDycore Timers Subsystem

The subsystem for timers and profiling is defined almost entirely in tdytimers.h.

When a dycore is initialized, a registry of timers is created when you call TDyInit(). Once this is done, you can manipulate timers with functions and macros as described below. Make sure you include the tdytimers.h file wherever you use these timers.

### Function-Level Profiling

The easiest way to use a timer is to instrument a function with a timer using TDY_START_FUNCTION_TIMER() and TDY_STOP_FUNCTION_TIMER(). These macros automatically create/retrieve a timer for the function and start/stop it as you’d expect. You place the START macro at the top of a function, and the STOP one at the bottom. For example::

void do_some_expensive_things(TDy dy)
{
TDY_START_FUNCTION_TIMER()
... // Do the expensive things
TDY_STOP_FUNCTION_TIMER()
}


There’s no need to understand PETSc’s logging objects–everything is done for you. These function-level timers are named after the functions in which they appear.

### Manually-Created Timers

Sometimes you want to time something that happens in the middle of a function. You can do this by calling the TDyGetTimer function with the TDyStartTimer and TDyStopTimer macros::

void do_various_things(TDy dy)
{
... // Stuff happens here

// Now we want to time a block of code in the middle of the function.
PetscLogEvent timer = TDyGetTimer("important things");
TDyStartTimer(timer);
... // Important things happen here!
TDyStopTimer(timer);

... // Other stuff happens here
}


This is a bit more involved–you need to know that timers are PetscLogEvent objects, for example, and you need to name your timers–but not too difficult. As you might have guessed, TDY_START_FUNCTION_TIMER and TDY_STOP_FUNCTION_TIMER are just wrappers around these constructs. TDyStartTimer and TDyStopTimer are themselves just macros that call PetscLogEventBegin and PetscLogEventEnd, so you can always use those if you want more control.

### Profiling Stages

PETSc allows an arbitrary number of logging/profiling “stages” to be defined so that you can organize your profiling into sections. These stages can be named for convenience. You can enter and exit a named stage with calls to TDyEnterProfilingStage(stageName) and TDyExitProfilingStage(stageName), where stageName is a string containing the name of the stage.

TDycore provides these named stages, registering them in TDyInit:

• "TDycore Setup": for creating meshes, setting up initial conditions, calculating time-independent matrices and vectors, etc.

• "TDycore Stepping", for timestepping

• "TDycore I/O", for checkpointing, restarting, generating visualizations

You can register your own named stages with TDyAddProfilingStage(stageName). All of this machinery is a thin wrapper around PETSc’s PetscLogStage mechanism, which you can use if you prefer. The functions and macros above just simplify the bookkeeping.

### Generating Profiling Logs

Adding timers to a code is only part of profiling. You also need to generate profiling reports for runs of interest! Fortunately, this is easy–just add the -tdy_timers flag to your command line arguments to generate a performance log. This log is named tdycore_profile.csv. It’s a comma-separated variable file containing all performance data collected by PETSc. The timers you’ve created show up in the profile just like those embedded in the PETSc library.

If you’d rather look at the traditional profiling/log data dumped by PETSc, you can use the -log_view flag to have PETSc print that information to the standard output.

### Interpreting Profile Data with TDyProf

If you’ve generated a tdycore_profile.csv file, you can use a tool called tdyprof (located in the tools/ subdirectory of the source tree). This Python script digests the contents of the CSV file you give it and generates nicely-formatted reports for desired information. Use it thus::

tdyprof <profile.csv> <command> [options]


or just type tdyprof by itself to see its usage information. For example, to see the top 10 “hotspots” in the performance profile::

tdyprof tdycore_profile.csv top10
tdyprof: showing top 10 hits:
Stage Name                               Event Name             Time             FLOP
Main Stage               TDyTimeIntegratorRunToTime         0.139049      1.85991e+07
Main Stage                                SNESSolve          0.13895      1.85991e+07
Main Stage                         SNESJacobianEval         0.120045          609812.
Main Stage              TDyMPFAOSNESJacobian_3DMesh         0.120032          609812.
Main Stage        TDyMPFAOIJacobian_Vertices_3DMesh         0.118853          606312.
TDycore Setup                   TDyDriverInitializeTDy        0.0912797           52040.
TDycore Setup                                 TDySetup        0.0533342           52040.
TDycore Setup                       TDyMPFAOInitialize        0.0533217           52040.
Main Stage                         DMPlexDistribute        0.0386017               0.
TDycore Setup                        TDyCreateJacobian        0.0370897               0.


TODO