Contributing to rocBLAS

Contributing to rocBLAS#

We welcome contributions to rocBLAS. Please follow these details to help ensure your contributions will be successfully accepted.

Issue Discussion#

Please use the GitHub Issues tab to notify us of issues.

Use your best judgment for issue creation. If your issue is already listed, upvote the issue and comment or post to provide additional details, such as how you reproduced this issue.
If you’re not sure if your issue is the same, err on the side of caution and file your issue. You can add a comment to include the issue number (and link) for the similar issue. If we evaluate your issue as being the same as the existing issue, we’ll close the duplicate.
If your issue doesn’t exist, use the issue template to file a new issue.
- When filing an issue, be sure to provide as much information as possible, including script output so we can collect information about your configuration. This helps reduce the time required to reproduce your issue.
- Check your issue regularly, as we may require additional information to successfully reproduce the issue.
You may also open an issue to ask questions to the maintainers about whether a proposed change meets the acceptance criteria, or to discuss an idea pertaining to the library.

Acceptance Criteria#

The aim of rocBLAS is to provide an optimized implementation of BLAS for ROCm. The library includes extensions like mixed precision and batched versions of functions.

Contributors wanting to submit new implementations, improvements, or bug fixes should follow the below mentioned guidelines.

Pull requests will be reviewed by members of CODEOWNERS.md Continuous Integration tests will be run on the pull request. Once the pull request is approved and tests pass it will be merged by a member of CODEOWNERS.md. Attribution for your commit will be preserved when it is merged.

Pull-request guidelines#

By creating a pull request, you agree to the statements made in the Code License section. Your pull request should target the default branch. Our current default branch is the develop branch, which serves as our integration branch.

Pull requests should:

ensure code builds successfully.
do not break existing test cases.
new functionality will only be merged with new unit tests.
new unit tests should integrate within the existing googletest framework.
tests must have good code coverage.
code must also have benchmark tests, and performance must approach. the compute bound limit or memory bound limit.

Code License#

All code contributed to this project will be licensed under the license identified in the LICENSE.md. Your contribution will be accepted under the same license.

For each new file in repository, please include the licensing header

/*******************************************************************************
 * Copyright (c) 20xx Advanced Micro Devices, Inc.
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to deal
 * in the Software without restriction, including without limitation the rights
 * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 * copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 *
 *******************************************************************************/

Coding Style#

rocBLAS code should avoid calling hipMalloc() or hipFree() within their code, as these are synchronizing APIs. Instead, users must rely on the rocBLAS device memory manager, which handles pre-allocated memory allocated during the creation of the rocBLAS handle.

rocBLAS device memory allocation system offers:
- A device_malloc() method in rocblas_handle for temporarily using device memory that has been either pre-allocated or allocated on demand.
- A method in rocblas_handle to reuse device memory across rocBLAS calls without allocating and deallocating for each call.
- A method in rocblas_handle for users to query the device memory required for optimal performance of a specific kernel call.
- A method in rocblas_handle for users to control the amount of device memory allocated or allow rocBLAS to handle on-demand allocation.
A rocBLAS function must allocate all of its device memory upfront for the entire duration of the function call and must not allocate and deallocate device memory at different kernel call levels. Lower-level kernels needing device memory must have it allocated by higher-level routines and passed down. When device memory can be shared between operations, the maximum size needed by all operations should be reported or allocated.

When allocating memory, use a variable name that indicates it is a workspace memory, such as workspace or with a w_ prefix, for example:
```
auto w_mem = handle->device_malloc(dev_bytes);
if(!w_mem)
{
    return rocblas_status_memory_error;
}
```
rocBLAS device memory manager also provides support for stream order allocation ( using hipMallocAsync() and hipFreeAsync() ).

For more information refer to rocBLAS Device Memory Allocation and Stream Order Allocation.
Logging, argument error checking and device memory allocation should only occur at the top-level API functions. Therefore, if one rocBLAS routine calls another, the lower-level internally called routine(s) should not perform logging, argument checking, or device memory allocation. This can be accomplished in one of two ways:

A. (Preferred.) Abstract out the computational part of the function that launches device kernels into a separate template (usually named rocblas_<function_name>_launcher), and call it from a higher-level template (usually named rocblas_<function_name>_impl) which does error-checking, device memory allocation, and logging, and which gets called by the C API level functions:
```
template <...>
rocblas_status rocblas_<function_name>_launcher(..., T* device_memory)
{
    // Performs fast computation
    // No argument error checking
    // No logging
    // No device memory allocation -- any temporary device memory must be passed in through pointers
    // Can be called by other computational functions
    // Called by rocblas_<function_name>_impl
    // Private internal API
}

template <...>
rocblas_status rocblas_<function_name>_impl()
{
    // Argument error checking
    // Logging
    // Responding to device memory size queries
    // Device memory allocation (through handle->device_malloc())
    // Temporarily switching to host pointer mode if scalar constants are used
    // Calls rocblas_<function_name>_launcher()
    // Private internal API
}

extern "C" rocblas_status rocblas_[hsdcz]<function_name>[_64]()
{
    // C wrapper
    // Calls rocblas_<function_name>_impl()
    // Public API
}
```
B. Use a bool template argument to specify if the kernel template should perform full functionality or not. Pass device memory pointer(s) which will be used if full functionality is turned off:
```
template <bool full_function, ...>
rocblas_status rocblas_<function_name>_launcher(..., T* device_memory = nullptr)
{
    if(full_function)
    {
        // Argument error checking
        // Logging
        // Responding to device memory size queries
        // Device memory allocation (memory pointer assumed already allocated otherwise)
        // Temporarily switching to host pointer mode if scalar constants are used
        return ROCBLAS_API(rocblas_<function_name>_launcher)<false, ...>(...);
    }
    // Perform fast computation
    // Private internal API
}
```
Device memory allocation, and temporarily switching pointer mode, might be difficult to enclose in an if statement with the RAII design, so the code might have to use recursion to call the non-fully-functional version of itself after setting these things up. That’s why method A above is preferred, but for some huge functions like GEMM, method B might be more practical to implement, since it disrupts existing code less.

When an internal API is exported for reuse, an additional template layer may be present between the _impl and _launcher templates (i.e. rocblas_<function_name>_template ). It may exist in a non batched and batched form. Additionally, when an ILP64 API is provided for a function, the above launcher template may end with an _64 suffix. The _impl template starts with an additional template typename API_INT which will be instantiated as either rocblas_int or int64_t. The macro ROCBLAS_API may be used to call the _64 or original form of a template instantiation.

For more information refer to the rocBLAS Programmers Guide
The pointer mode should be temporarily switched to host mode during kernels which pass constants to other kernels, so that host-side constants of -1.0, 0.0 and 1.0 can be passed to kernels like GEMM, without causing synchronizing host<->device memory copies. For example:
```
// Temporarily switch to host pointer mode, saving current pointer mode, restored on return
auto saved_pointer_mode = handle->push_pointer_mode(rocblas_pointer_mode_host);

// Get alpha
T alpha_h;
if(saved_pointer_mode == rocblas_pointer_mode_host)
    alpha_h = *alpha;
else
    RETURN_IF_HIP_ERROR(hipMemcpy(&alpha_h, alpha, sizeof(T), hipMemcpyDeviceToHost));
```
saved_pointer_mode can be read to get the old pointer mode. If the old pointer mode was host pointer mode, then the host pointer is dereferenced to get the value of alpha. If the old pointer mode was device pointer mode, then the value of alpha is copied from the device to the host.

After the above code switches to host pointer mode, constant values can be passed to GEMM or other kernels by always assuming host mode:
```
static constexpr T negative_one = -1;
static constexpr T zero = 0;
static constexpr T one = 1;

rocblas_internal_gemm_template( handle, transA, transB, jb, n, jb, alpha, invA, BLOCK, B, ldb, &zero, X, m);
```
When saved_pointer_mode is destroyed, the handle’s pointer mode returns to the previous pointer mode.
When tests are added to rocblas-test and rocblas-bench, refer to this guide.

The test framework is templated, and uses SFINAE (substitution failure is not an error) pattern and std::enable_if<...> to enable and disable certain types for certain tests.

YAML files are used to describe tests as combinations of arguments. rocblas_gentest.py is used to parse the YAML files and generate tests in the form of a binary file of Arguments records.

The rocblas-test and rocblas-bench type dispatch file is central to all tests. Basically, rather than duplicate:
```
if(type == rocblas_datatype_f16_r)
    func1<rocblas_half>(args);
else if(type == rocblas_datatype_f32_r)
    func<float>(args);
else if(type == rocblas_datatype_f64_r)
    func<double>(args);
```
etc. everywhere, it’s done only in one place, and a template template argument is passed to specify which action is actually taken. It’s fairly abstract, but it is powerful. There are examples of using the type dispatch in clients/gtest/*_gtest.cpp and clients/benchmarks/client.cpp.
Code should not be copied-and pasted, but rather, templates, macros, SFINAE (substitution failure is not an error) pattern and CRTP (curiously recurring template pattern), etc. should be used to factor out differences in similar code.

A code should be made more generalized, rather than copied and modified, unless it is a completely different kernel function, and the old code is just being used as a start.

If a new function is similar to an existing function, then the existing function should be generalized, or the new function and existing function should be refactored and based on a third templated function or class, rather than duplicating code.
To differentiate between scalars located on either the host or device memory, a special function has been created, called load_scalar(). If its argument is a pointer, it is dereferenced on the device. If the argument is a scalar, it is simply copied. This allows single HIP kernels to be written for both device and host memory:
```
template <typename T, typename U>
ROCBLAS_KERNEL void axpy_kernel(rocblas_int n, U alpha_device_host, const T* x, rocblas_int incx, T* y, rocblas_int incy)
{
    auto alpha = load_scalar(alpha_device_host);
    ptrdiff_t tid = blockIdx.x * blockDim.x + threadIdx.x;

   // bound
   if(tid < n)
       y[tid * incy] += alpha * x[tid * incx];
}
```
Here, alpha_device_host can either be a pointer to device memory, or a numeric value passed directly to the kernel from the host. The load_scalar() function dereferences it if it’s a pointer to device memory, and simply returns its argument if it’s numerical. The kernel is called from the host in one of two ways depending on the pointer mode:
```
if(handle->pointer_mode == rocblas_pointer_mode_device)
    ROCBLAS_LAUNCH_KERNEL(axpy_kernel, blocks, threads, 0, handle->get_stream(), n, alpha, x, incx, y, incy);
else if(*alpha) // alpha is on host
    ROCBLAS_LAUNCH_KERNEL(axpy_kernel, blocks, threads, 0, handle->get_stream(), n, *alpha, x, incx, y, incy);
```
When the pointer mode indicates alpha is on the host, the alpha pointer is dereferenced on the host and the numeric value it points to is passed to the kernel. When the pointer mode indicates alpha is on the device, the alpha pointer is passed to the kernel and dereferenced by the kernel on the device. This allows a single kernel to handle both cases, eliminating duplicate code.
If new arithmetic datatypes (like rocblas_bfloat16) are created, then unless they correspond exactly to a predefined system type, they should be wrapped into a struct, and not simply be a typedef to another type of the same size, so that their type is unique and can be differentiated from other types.

Right now rocblas_half is typedefed to uint16_t, which unfortunately prevents rocblas_half and uint16_t from being differentiable. If rocblas_half were simply a struct with a uint16_t member, then it would be a distinct type.

It is legal to convert a pointer to a standard-layout class/struct to a pointer to its first element, and vice-versa, so the C API is unaffected by whether the type is enclosed in a struct or not.
RAII (resource acquisition is initialization) patterned classes should be used instead of explicit new/delete, hipMalloc/hipFree, malloc/free, etc. RAII classes are automatically exception-safe because their destructor gets called during unwinding. They only have to be declared once to construct them, and they are automatically destroyed when they go out of scope. This is better than having to match new/delete malloc/free calls in the code, especially when exceptions or early returns are possible.

Even if an operation does not allocate and free memory, if it represents a change in state which must be undone when a function returns, then it belongs in an RAII class. For example, handle->push_pointer_mode() creates an RAII object which saves the pointer mode on construction, and restores it on destruction.

When writing function templates, place any non-type parameters before type parameters, i.e., leave the type parameters at the end. For example:

template <rocblas_int NB, typename T> // T is at end
static rocblas_status rocblas_trtri_batched_template(rocblas_handle handle,
                                                     rocblas_fill uplo,
                                                     rocblas_diagonal diag,
                                                     rocblas_int n,
                                                     const T* A,
                                                     rocblas_int lda,
                                                     rocblas_int bsa,
                                                     T* invA,
                                                     rocblas_int ldinvA,
                                                     rocblas_int bsinvA,
                                                     rocblas_int batch_count,
                                                     T* C_tmp)
{
    if(!n || !batch_count)
        return rocblas_status_success;

     if(n <= NB)
         return rocblas_trtri_small_batched<NB>(  // T is automatically deduced
             handle, uplo, diag, n, A, lda, bsa, invA, ldinvA, bsinvA, batch_count);
     else
         return rocblas_trtri_large_batched<NB>(  // T is automatically deduced
             handle, uplo, diag, n, A, lda, bsa, invA, ldinvA, bsinvA, batch_count, C_tmp);
}

The reason for this, is that the type template arguments can be automatically deduced from the actual function arguments, so that you don’t have to pass the types in calls to the function, as shown in the example above when calling rocblas_trtri_small_batched and rocblas_trtri_large_batched. They have a typename T parameter too, but it can be automatically deduced, so it doesn’t need to be explicitly passed.

When writing functions like the above which are heavily dependent on block sizes, especially if they are in header files included by other files, template parameters for block sizes are strongly preferred to #define macros or constexpr variables. For .cpp files which are not included in other files, a static constexpr variable can be used. Macros should never be used for constants.

Note: For constants inside of functions, static constexpr is preferred to just constexpr, so that the variables do not need to be initialized at runtime.

Note: C++14 variable templates can sometimes be used to provide constants. For example:
```
template <typename T>
static constexpr T negative_one = -1;

template <typename T>
static constexpr T zero = 0;

template <typename T>
static constexpr T one = 1;
```
static duration variables which aren’t constants should usually be made function-local static variables, rather than namespace or class static variables. This is to avoid the static initialization order fiasco. For example:
```
static auto& get_table()
{
    // Placed inside function to avoid dependency on initialization order
    static std::unordered_map<std::string, size_t>* table = test_cleanup::allocate(&table);
    return *table;
}
```
This is sometimes called the singleton pattern. A static variable is made local to a function rather than a namespace or class, and it gets initialized the first time the function is called. A reference to the static variable is returned from the function, and the function is used everywhere access to the variable is needed. In the case of multithreaded programs, the C++11 and later standards guarantee that there won’t be any race conditions. It is preferred to initialize function-local static variables than it is to explicitly call std::call_once. For example:
```
void my_func()
{
    static int dummy = (func_to_call_once(), 0);
}
```
This is much simpler and faster than explicitly calling std::call_once, since the compiler has special ways of optimizing static initialization. The first time my_func() is called, it will call func_to_call_once() once in a thread-safe way. After that, there is almost no overhead in later calls to my_func().
Functions are preferred to macros. Functions or functors inside of class / struct templates can be used when partial template specializations are needed.

When C preprocessor macros are needed (such as if they contain a return statement to return from the calling function), if the macro’s definition contains more than one simple expression, then it should be wrapped in a do { } while(0), without a terminating semicolon. This is to allow them to be used inside if statements. For example:
```
#define RETURN_ZERO_DEVICE_MEMORY_SIZE_IF_QUERIED(h) \
    do                                               \
    {                                                \
        if((h)->is_device_memory_size_query())       \
            return rocblas_status_size_unchanged;    \
    } while(0)
```
The do { } while(0) allows the macro expansion to be a single statement which can be terminated with a semicolon, and which can be used anywhere a regular function call can be used.
For most template functions which are used in other compilation units, it is preferred that they be put in header files, rather than .cpp files, because putting them in .cpp files requires explicit instantiation of them for all possible arguments, and there are less opportunities for inlining and interprocedural optimization.

The C++ standard explicitly says that unused templates can be omitted from the output, so including unused templates in a header file does not increase the size of the program, since only the used ones are in the final output.

For template functions which are only used in one .cpp file, they can be placed in the .cpp file.

Templates, like inline functions, are granted an exception to the one definition rule (ODR) as long as the sequence of tokens in each compilation unit is identical.
Functions and namespace-scope variables which are not a part of the public interface of rocBLAS, should either be marked static, be placed in an unnamed namespace, or be placed in namespace rocblas. For example:
```
namespace
{
    // Private internal implementation
} // namespace

extern "C"
{
    // Public C interfaces
} // extern "C"
```
However, unnamed namespaces should not be used in header files. If it is absolutely necessary to mark a function or variable as private to a compilation unit but defined in a header file, it should be declared static, constexpr and/or inline (constexpr implies static for non-template variables and inline for functions).

Even though rocBLAS goes into a shared library which exports a limited number of symbols, this is still a good idea, to decrease the chances of name collisions inside of rocBLAS.
std::string should only be used for strings which can grow, or which must be dynamically allocated as read-write strings. For simple static strings, strings returned from functions like getenv(), or strings which are initialized once and then used read-only, const char* should be used to refer to the string or pass it as an argument.

std::string involves dynamic memory allocation and copying of temporaries, which can be slow. std::string_view is supposed to help alleviate that, which became available in C++17. const char* can be used for read-only views of strings, in the interest of efficiency.
For code brevity and readability, when converting to numeric types, uniform initialization or function-style casts are preferred to static_cast<>() or C-style casts. For example, T{x} or T(x) is preferred to static_cast<T>(x) or (T)x. T{x} differs from T(x) in that narrowing conversions, which reduce the precision of an integer or floating-point, are not allowed.

When writing general containers or templates which can accept arbitrary types as parameters, not just numeric types, then the specific cast (static_cast, const_cast, reinterpret_cast) should be used, to avoid surprises.

But when converting to numeric types, which have very well-understood behavior and are side-effect free, type{x} or type(x) are more compact and clearer than static_cast<type>(x). For pointers, C-style casts are okay, such as (T*)A.
For BLAS2 functions and BLAS1 functions with two vectors, the incx and/or incy arguments can be negative, which means the vector is treated backwards from the end. A simple trick to handle this, is to adjust the pointer to the end of the vector if the increment is negative, as in:
```
if(incx < 0)
    x -= ptrdiff_t(incx) * (n - 1);
if(incy < 0)
    y -= ptrdiff_t(incy) * (n - 1);
```
After that adjustment, the code does not need to treat negative increments any differently than positive ones.

Note: Some blocked matrix-vector algorithms which call other BLAS kernels may not work if this simple transformation is used; see TRSV for an example, and how it’s handled there.
For reduction operations, the file reduction.hpp <https://github.com/ROCm/rocBLAS/blob/develop/library/src/blas1/reduction.hpp> has been created to systematize reductions and perform their device kernels in one place. This works for amax, amin, asum, nrm2, and (partially) dot and gemv. rocblas_reduction_kernel is a generalized kernel which takes 3 functors as template arguments:
- One to fetch values (such as fetching a complex value and taking the sum of the squares of its real and imaginary parts before reducing it)
- One to reduce values (such as to compute a sum or maximum)
- One to finalize the reduction (such as taking the square root of a sum of squares)
There is a default_value() function which returns the default value for a reduction. The default value is the value of the reduction when the size is 0, and reducing a value with the default_value() does not change the value of the reduction.

When type punning is needed, union should be used instead of pointer-casting, which violates strict aliasing. For example:

// zero extend lower 16 bits of bfloat16 to convert to IEEE float
explicit __host__ __device__ operator float() const
{
    union
    {
        uint32_t int32;
        float    fp32;
    } u = {uint32_t(data) << 16};
    return u.fp32; // Legal in C, nonstandard extension in C++
}

This violates the strict aliasing rule of C and C++:

// zero extend lower 16 bits of bfloat16 to convert to IEEE float
explicit __host__ __device__ operator float() const
{
    uint32_t int32 = uint32_t(data) << 16;
    return *(float *) &int32; // Violates strict aliasing rule in both C and C++
}

The only 100% standard C++ way to do it, is to use memcpy(), but this should not be required as long as GCC or Clang are used:

// zero extend lower 16 bits of bfloat16 to convert to IEEE float
explicit __host__ __device__ operator float() const
{
    uint32_t int32 = uint32_t(data) << 16;
    float fp32;
    static_assert(sizeof(int32) == sizeof(fp32), "Different sizes");
    memcpy(&fp32, &int32, sizeof(fp32));
    return fp32;
}

<type_traits> classes which return Boolean values can be converted to bool in Boolean contexts. Hence many traits can be tested by simply creating an instance of them with {}. However, for type_traits accessors such as ::value or ::type, these can be replaced by suffixes added in C++17 such as is_same_v and enable_if_t:
```
template<typename T, typename = typename std::enable_if_t<std::is_same_v<T, float> ||
                                                          std::is_same_v<T, double>>>
void function(T x)
{
}
```
For other traits created with the {} syntax the resulting temporary objects can be explicitly converted to bool, which is what occurs when an object appears in a conditional expression (if, while, for, &&, ||, !, ? :, etc.).
rocblas_cout and rocblas_cerr should be used instead of std::cout, std::cerr, stdout or stderr, and rocblas_internal_ostream should be used instead of std::ostream, std::ofstream or std::ostringstream.

In rocblas-bench and rocblas-test, std::cout, std::cerr, printf, fprintf, stdout, stderr, puts(), fputs(), and other symbols are “poisoned”, to remind you to use rocblas_cout, rocblas_cerr, and rocblas_internal_ostream instead.

rocblas_cout and rocblas_cerr are instances of rocblas_internal_ostream which output to standard output and standard error, but in a way that prevents interlacing of different threads’ output.

rocblas_internal_ostream provides standardized thread-safe formatted output for rocBLAS datatypes. It can be constructed in 3 ways: - By default, in which case it behaves like a std::ostringstream - With a file descriptor number, in which case the file descriptor is dup()``ed and the same file it points to is outputted to - With a string, in which case a new file is opened for writing, with file creation, truncation and appending enabled (``O_WRONLY | O_CREAT | O_TRUNC | O_APPEND | O_CLOEXEC)

std::endl or std::flush should be used at the end of an output sequence when an atomic flush of the output is needed (atomic meaning that multiple threads can be writing to the same file, but that their flushes will be atomic). Until then, the output will accumulate in the rocblas_internal_ostream and will not be flushed until either rocblas_internal_ostream::flush() is called, std::endl or std::flush is outputted, or the rocblas_internal_ostream is destroyed.

The rocblas_internal_ostream::yaml_on and rocblas_internal_ostream::yaml_off IO modifiers enable or disable YAML formatting, for when outputting abitrary types as YAML source code. For example, to output a key: value pair as YAML source code, you would use:
```
os << key << ": " << rocblas_internal_ostream::yaml_on << value << rocblas_internal_ostream::yaml_off;
```
The key is outputted normally as a bare string, but the value uses YAML metacharacters and lexical syntax to output the value, so that when it’s read in as YAML, it has the type and value of value.
C++ templates, including variadic templates, are preferred to macros or runtime interpreting of values, although it is understood that sometimes macros are necessary.

For example, when creating a class which models zero or more rocBLAS kernel arguments, it is preferable to use:
```
template<rocblas_argument... Args>
class ArgumentModel
{
    public:
        void func()
        {
            for(auto arg: { Args... })
            {
                //do something with argument arg
            }
        }
};
ArgumentModel<e_A, e_B>{}.func();
```
instead of:
```
class ArgumentModel
{
    std::vector<rocblas_argument> args;
    public:
        ArgumentModel(const std::vector<rocblas_argument>& args): args(args)
        {
        }

        void func()
        {
            for(auto arg: args)
            {
                //do something with argument arg
            }
        }
};
ArgumentModel model({e_A, e_B});
model.func();
```
The former denotes the rocBLAS arguments as a list which is passed as a variadic template argument, and whose properties are known and can be optimized at compile-time, and which can be passed on as arguments to other templates, while the latter requires creating a dynamically-allocated runtime object which must be interpreted at runtime, such as by using switch statements on the arguments. The switch statement will need to list out and handle every possible argument, while the template solution simply passes the argument as another template argument, and hence can be resolved at compile-time.
Automatically-generated files should always go into build/ directories, and should not go into source directories (even if marked .gitignore). The CMake philosophy is such that you can create any build/ directory, run cmake from there, and then have a self-contained build environment which will not touch any files outside of it.
The library/include subdirectory of rocBLAS, to be distinguished from the library/src/include subdirectory, shall consist only of C-compatible header files for public rocBLAS APIs. It should not include internal APIs, even if they are used in other projects, e.g., rocSOLVER, and the headers must be compilable with a C compiler, and must use .h extensions.
Macro parameters should only be evaluated once when practical, and should be parenthesized if there is a chance of ambiguous precedence. They should be stored in a local temporary variable if needed more than once.

Macros which expand to code with local variables, should use double-underscore suffixes in the local variable names, to prevent their conflict with variables passed in macro parameters. However, if they are in a completely separate block scope than the macro parameter is expanded in, or if they are only passed to another macro/function, then they do not need to use trailing underscores.
```
#define CHECK_DEVICE_ALLOCATION(ERROR)                   \
    do                                                   \
    {                                                    \
        /* Use error__ in case ERROR contains "error" */ \
        hipError_t error__ = (ERROR);                    \
        if(error__ != hipSuccess)                        \
        {                                                \
            if(error__ == hipErrorOutOfMemory)           \
                GTEST_SKIP() << LIMITED_VRAM_STRING;     \
            else                                         \
                FAIL() << hipGetErrorString(error__);    \
            return;                                      \
        }                                                \
    } while(0)
```
The ERROR macro parameter is evaluated only once, and is stored in the temporary variable error__, for use multiple times later.

The ERROR macro parameter is parenthesized when initializing error__, to avoid ambiguous precedence, such as if ERROR contains a comma expression.

The error__ variable name is used, to prevent it from conflicting with variables passed in the ERROR macro parameter, such as error.

Do not use variable-length arrays (VLA), which allocate on the stack, for arrays of unknown size.

Ti* hostA[batch_count];
Ti* hostB[batch_count];
To* hostC[batch_count];
To* hostD[batch_count];

func(hostA, hostB, hostC, hostD);

Instead, allocate on the heap, using smart pointers to avoid memory leaks:

auto hostA = std::make_unique<Ti*[]>(batch_count);
auto hostB = std::make_unique<Ti*[]>(batch_count);
auto hostC = std::make_unique<To*[]>(batch_count);
auto hostD = std::make_unique<To*[]>(batch_count);

func(&hostA[0], &hostB[0], &hostC[0], &hostD[0]);

Do not define unnamed (anonymous) namespaces in header files (for explanation see DCL59-CPP)

If the reason for using an unnamed namespace in a header file is to prevent multiple definitions, keep in mind that the following are allowed to be defined in multiple compilation units, such as if they all come from the same header file, as long as they are defined with identical token sequences in each compilation unit:
- classes
- typedefs or type aliases
- enums
- template functions
- inline functions
- constexpr functions (implies inline)
- inline or constexpr variables or variable template``s (only for C++17 or later, although some C++14 compilers treat ``constexpr variables as inline)
If functions defined in header files are declared template, then multiple instantiations with the same template arguments are automatically merged, something which cannot happen if the template functions are declared static, or appear in unnamed namespaces, in which case the instantiations are local to each compilation unit, and are not combined.

If a function defined in a header file at namespace scope (outside of a class) contains static _local variables which are expected to be singletons holding state throughout the entire library, then the function cannot be marked static or be part of an unnamed namespace, because then each compilation unit will have its own separate copy of that function and its local static variables. (static member functions of classes always have external linkage, and it is okay to define static class member functions in-place inside of header files, because all in-place static member function definitions, including their static local variables, will be automatically merged.)

Guidelines:

Do not use unnamed namespaces inside of header files.
Use either template or inline (or both) for functions defined outside of classes in header files.
Do not declare namespace-scope (not class-scope) functions static inside of header files unless there is a very good reason, that the function does not have any non-const static local variables, and that it is acceptable that each compilation unit will have its own independent definition of the function and its static local variables. (static class member functions defined in header files are okay.)
Use static for constexpr template variables until C++17, after which constexpr variables become inline variables, and thus can be defined in multiple compilation units. It is okay if the constexpr variables remain static in C++17; it just means there might be a little bit of redundancy between compilation units.

Process#

rocBLAS uses the clang-format tool for formatting C and C++ code. To format a file, use:

clang-format -style=file -i <path-to-source-file>

To format all files, run the following script in rocBLAS directory:

#!/bin/bash
git ls-files -z *.cc *.cpp *.h *.hpp *.cl *.h.in *.hpp.in *.cpp.in | xargs -0 clang-format -style=file -i

Also, githooks can be installed to format the code per-commit:

./.githooks/install

cppcheck is an open-source static analysis tool. This project uses this tool for performing static code analysis.

Users can use the following command to run cppcheck locally to generate the report for all files.

$ cd rocBLAS-internal
$ cppcheck --enable=all --inconclusive --library=googletest --inline-suppr -i./build --suppressions-list=./CppCheckSuppressions.txt --template="{file}:{line}: {severity}: {id} :{message}" . 2> cppcheck_report.txt

Also, githooks can be installed to perform static analysis on new/modified files using pre-commit:

./.githooks/install

For more information on the command line options, refer to the cppcheck manual on the web.

References#

rocBLAS documentation

Contributing to rocBLAS

Contents

Contributing to rocBLAS#