kernel.hpp

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#pragma once
#ifndef CUDA_API_WRAPPERS_KERNEL_HPP_
#define CUDA_API_WRAPPERS_KERNEL_HPP_

#include "primary_context.hpp"
#include "current_context.hpp"
#include "error.hpp"
#include "types.hpp"

#if CUDA_VERSION < 11000
#define CAN_GET_APRIORI_KERNEL_HANDLE 0
#define VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE virtual
#else
#define CAN_GET_APRIORI_KERNEL_HANDLE 1
#define VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
#endif

namespace cuda {

class kernel_t;

namespace kernel {

using shared_memory_size_determiner_t = size_t (CUDA_CB *)(int block_size);

kernel_t wrap(
    device::id_t       device_id,
    context::handle_t  context_id,
    kernel::handle_t   f,
    bool               hold_primary_context_refcount_unit = false);

namespace detail_ {

inline ::std::string identify(const kernel_t& kernel);

static const char* attribute_name(int attribute_index)
{
    // Note: These correspond to the values of enum CUfunction_attribute_enum
    static const char* names[] = {
        "Maximum number of threads per block",
        "Statically-allocated shared memory size in bytes",
        "Required constant memory size in bytes",
        "Required local memory size in bytes",
        "Number of registers used by each thread",
        "PTX virtual architecture version into which the kernel code was compiled",
        "Binary architecture version for which the function was compiled",
        "Indication whether the function was compiled with cache mode CA",
        "Maximum allowed size of dynamically-allocated shared memory use size bytes",
        "Preferred shared memory carve-out to actual shared memory"
    };
    return names[attribute_index];
}

inline attribute_value_t get_attribute_in_current_context(handle_t handle, attribute_t attribute)
{
    kernel::attribute_value_t attribute_value;
    auto result = cuFuncGetAttribute(&attribute_value,  attribute, handle);
    throw_if_error_lazy(result, ::std::string("Failed obtaining attribute ") + attribute_name(attribute));
    return attribute_value;
}

inline void set_attribute_in_current_context(handle_t handle, attribute_t attribute, attribute_value_t value)
{
#if CUDA_VERSION >= 9000
    auto result = cuFuncSetAttribute(handle, static_cast<CUfunction_attribute>(attribute), value);
    throw_if_error_lazy(result,
        "Setting CUDA device function attribute " +
        ::std::string(kernel::detail_::attribute_name(attribute)) + " of function at "
        + cuda::kernel::detail_::identify(handle) + " to value " + ::std::to_string(value));
#else
    throw(cuda::runtime_error {cuda::status::not_yet_implemented});
#endif
}

} // namespace detail_

inline attribute_value_t get_attribute(const kernel_t& kernel, attribute_t attribute);

} // namespace kernel

class kernel_t {

public: // getters
    context_t context() const noexcept;
    device_t device() const noexcept;

    device::id_t device_id() const noexcept { return device_id_; }
    context::handle_t context_handle() const noexcept { return context_handle_; }
#if CAN_GET_APRIORI_KERNEL_HANDLE
    kernel::handle_t handle() const noexcept { return handle_; }
#else
    kernel::handle_t handle() const
    {
#ifndef NDEBUG
        if (handle_ == nullptr) {
            throw runtime_error(status::named_t::invalid_resource_handle,
                "CUDA driver handle unavailable for kernel");
        }
#endif
        return handle_;
    }
#endif

public: // operators

    kernel_t& operator=(const kernel_t&) = delete;
    kernel_t& operator=(kernel_t&& other) noexcept
    {
        ::std::swap(device_id_, other.device_id_);
        ::std::swap(context_handle_, other.context_handle_);
        ::std::swap(handle_, other.handle_);
        ::std::swap(holds_pc_refcount_unit, holds_pc_refcount_unit);
        return *this;
    }


public: // non-mutators

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    kernel::attribute_value_t get_attribute(kernel::attribute_t attribute) const
    {
        return kernel::get_attribute(*this, attribute);
    }

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    cuda::device::compute_capability_t ptx_version() const
    {
        auto raw_attribute = get_attribute(CU_FUNC_ATTRIBUTE_PTX_VERSION);
        return device::compute_capability_t::from_combined_number(raw_attribute);
    }

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    cuda::device::compute_capability_t binary_compilation_target_architecture() const {
        auto raw_attribute = get_attribute(CU_FUNC_ATTRIBUTE_BINARY_VERSION);
        return device::compute_capability_t::from_combined_number(raw_attribute);
    }

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    grid::block_dimension_t maximum_threads_per_block() const
    {
        return get_attribute(CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK);
    }

#if CUDA_VERSION >= 10000

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    grid::composite_dimensions_t min_grid_params_for_max_occupancy(
        memory::shared::size_t dynamic_shared_memory_size = no_dynamic_shared_memory,
        grid::block_dimension_t block_size_limit = 0,
        bool disable_caching_override = false) const;

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    grid::composite_dimensions_t min_grid_params_for_max_occupancy(
        kernel::shared_memory_size_determiner_t  shared_memory_size_determiner,
        grid::block_dimension_t                  block_size_limit = 0,
        bool                                     disable_caching_override = false) const;
#endif // CUDA_VERSION >= 10000

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    grid::dimension_t max_active_blocks_per_multiprocessor(
        grid::block_dimension_t block_size_in_threads,
        memory::shared::size_t  dynamic_shared_memory_per_block,
        bool                    disable_caching_override = false) const;



public: // methods mutating the kernel-in-context, but not this reference object

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    void set_attribute(kernel::attribute_t attribute, kernel::attribute_value_t value) const;

    void set_maximum_dynamic_shared_memory_per_block(cuda::memory::shared::size_t amount_required_by_kernel) const
    {
        auto amount_required_by_kernel_ = static_cast<kernel::attribute_value_t>(amount_required_by_kernel);
        if (amount_required_by_kernel != static_cast<cuda::memory::shared::size_t>(amount_required_by_kernel_)) {
            throw ::std::invalid_argument("Requested amount of maximum shared memory exceeds the "
                "representation range for kernel attribute values");
        }
        // TODO: Consider a check in debug mode for the value being within range
        set_attribute(CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES,amount_required_by_kernel_);
    }

    memory::shared::size_t get_maximum_dynamic_shared_memory_per_block() const
    {
        return get_attribute(CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES);
    }

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    void set_cache_preference(multiprocessor_cache_preference_t preference) const
    {
        context::current::detail_::scoped_override_t set_context_for_this_context(context_handle_);
        auto result = cuFuncSetCacheConfig(handle(), static_cast<CUfunc_cache>(preference));
        throw_if_error_lazy(result,
            "Setting the multiprocessor L1/Shared Memory cache distribution preference for a "
            "CUDA device function");
    }

    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    void set_shared_memory_bank_size(multiprocessor_shared_memory_bank_size_option_t config) const
    {
        // TODO: Need to set a context, not a device
        context::current::detail_::scoped_override_t set_context_for_this_context(context_handle_);
        auto result = cuFuncSetSharedMemConfig(handle(), static_cast<CUsharedconfig>(config) );
        throw_if_error_lazy(result, "Failed setting the shared memory bank size");
    }

protected: // ctors & dtor
    kernel_t(
        device::id_t       device_id,
        context::handle_t  context_handle,
        kernel::handle_t   handle,
        bool               hold_primary_context_refcount_unit)
     :
        device_id_(device_id),
        context_handle_(context_handle),
        handle_(handle),
        holds_pc_refcount_unit(hold_primary_context_refcount_unit)
    { }

public: // ctors & dtor
    friend kernel_t kernel::wrap(device::id_t, context::handle_t, kernel::handle_t, bool);

    kernel_t(const kernel_t& other) :
        kernel_t(other.device_id_, other.context_handle_, other.handle_, false) { }

    kernel_t(kernel_t&& other) :
        kernel_t(other.device_id_, other.context_handle_, other.handle_, false)
    {
        ::std::swap(holds_pc_refcount_unit, other.holds_pc_refcount_unit);
    }

public: // ctors & dtor
    VIRTUAL_UNLESS_CAN_GET_APRIORI_KERNEL_HANDLE
    ~kernel_t() NOEXCEPT_IF_NDEBUG
    {
        // TODO: DRY
        if (holds_pc_refcount_unit) {
#ifdef NDEBUG
            device::primary_context::detail_::decrease_refcount_nothrow(device_id_);
                // Note: "Swallowing" any potential error to avoid ::std::terminate(); also,
                // because a failure probably means the primary context is inactive already
#else
            device::primary_context::detail_::decrease_refcount(device_id_);
#endif
        }
    }

protected: // data members
    device::id_t device_id_; // We don't _absolutely_ need the device ID, but - why not have it if we can?
    context::handle_t context_handle_;
    mutable kernel::handle_t handle_;
    bool holds_pc_refcount_unit;
}; // kernel_t

namespace kernel {

inline kernel_t wrap(
    device::id_t       device_id,
    context::handle_t  context_id,
    kernel::handle_t   f,
    bool hold_primary_context_refcount_unit)
{
    return kernel_t{ device_id, context_id, f, hold_primary_context_refcount_unit };
}

inline attribute_value_t get_attribute(const kernel_t& kernel, attribute_t attribute)
{
    CAW_SET_SCOPE_CONTEXT(kernel.context_handle());
    return detail_::get_attribute_in_current_context(kernel.handle(), attribute);
}

inline void set_attribute(const kernel_t& kernel, attribute_t attribute, attribute_value_t value)
{
    CAW_SET_SCOPE_CONTEXT(kernel.context_handle());
    return detail_::set_attribute_in_current_context(kernel.handle(), attribute, value);
}

inline attribute_value_t set_attribute(const kernel_t& kernel, attribute_t attribute)
{
    CAW_SET_SCOPE_CONTEXT(kernel.context_handle());
    return kernel::detail_::get_attribute_in_current_context(kernel.handle(), attribute);
}

namespace occupancy {

namespace detail_ {

inline grid::dimension_t max_active_blocks_per_multiprocessor(
    handle_t                handle,
    grid::block_dimension_t block_size_in_threads,
    memory::shared::size_t  dynamic_shared_memory_per_block,
    bool                    disable_caching_override)
{
    int result;
        // We don't need the initialization, but NVCC backed by GCC 8 warns us about it.
    auto flags = static_cast<unsigned>(disable_caching_override) ? CU_OCCUPANCY_DISABLE_CACHING_OVERRIDE : CU_OCCUPANCY_DEFAULT;
    cuda::status_t status = cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags(
        &result, handle, static_cast<int>(block_size_in_threads), dynamic_shared_memory_per_block, flags);
    throw_if_error_lazy(status,
        "Determining the maximum occupancy in blocks per multiprocessor, given the block size and the amount of dynamic memory per block");
    return result;
}

#if CUDA_VERSION >= 10000
// Note: If determine_shared_mem_by_block_size is not null, fixed_shared_mem_size is ignored;
// if block_size_limit is 0, it is ignored.
inline grid::composite_dimensions_t min_grid_params_for_max_occupancy(
    CUfunction                     kernel_handle,
    cuda::device::id_t             device_id,
    CUoccupancyB2DSize             determine_shared_mem_by_block_size,
    cuda::memory::shared::size_t   fixed_shared_mem_size,
    cuda::grid::block_dimension_t  block_size_limit,
    bool                           disable_caching_override)
{
    int min_grid_size_in_blocks { 0 };
    int block_size { 0 };
    // Note: only initializing the values her because of a
    // spurious (?) compiler warning about potential uninitialized use.

    auto result =  cuOccupancyMaxPotentialBlockSizeWithFlags(
        &min_grid_size_in_blocks, &block_size,
        kernel_handle,
        determine_shared_mem_by_block_size,
        fixed_shared_mem_size,
        static_cast<int>(block_size_limit),
        disable_caching_override ? CU_OCCUPANCY_DISABLE_CACHING_OVERRIDE : CU_OCCUPANCY_DEFAULT
    );

    throw_if_error_lazy(result,
        "Failed obtaining parameters for a minimum-size grid for " + kernel::detail_::identify(kernel_handle, device_id)
        + " with maximum occupancy given dynamic shared memory and block size data");
    return { static_cast<grid::dimension_t>(min_grid_size_in_blocks), static_cast<grid::block_dimension_t>(block_size) };
}
#endif // CUDA_VERSION >= 10000

} // namespace detail_

#if CUDA_VERSION >= 11000

inline memory::shared::size_t max_dynamic_shared_memory_per_block(
    const kernel_t &kernel,
    grid::dimension_t blocks_on_multiprocessor,
    grid::block_dimension_t block_size_in_threads)
{
    size_t result;
    auto status = cuOccupancyAvailableDynamicSMemPerBlock(
        &result, kernel.handle(), static_cast<int>(blocks_on_multiprocessor), static_cast<int>(block_size_in_threads));
    throw_if_error_lazy(status, "Determining the available dynamic memory per block, given "
        "the number of blocks on a multiprocessor and their size");
    return static_cast<memory::shared::size_t>(result);
}
#endif // CUDA_VERSION >= 11000

inline grid::dimension_t max_active_blocks_per_multiprocessor(
    const kernel_t &kernel,
    grid::block_dimension_t block_size_in_threads,
    memory::shared::size_t dynamic_shared_memory_per_block,
    bool disable_caching_override = false);

} // namespace occupancy

namespace detail_ {

inline ::std::string identify(const kernel_t& kernel)
{
    return kernel::detail_::identify(kernel.handle()) + " in " + context::detail_::identify(kernel.context());
}

} // namespace detail_

} // namespace kernel

#if CUDA_VERSION >= 10000
inline grid::composite_dimensions_t kernel_t::min_grid_params_for_max_occupancy(
    memory::shared::size_t   dynamic_shared_memory_size,
    grid::block_dimension_t  block_size_limit,
    bool                     disable_caching_override) const
{
    kernel::shared_memory_size_determiner_t no_shared_memory_size_determiner { nullptr };
    return kernel::occupancy::detail_::min_grid_params_for_max_occupancy(
        handle(), device_id(), no_shared_memory_size_determiner,
        dynamic_shared_memory_size, block_size_limit, disable_caching_override);
}

inline grid::composite_dimensions_t kernel_t::min_grid_params_for_max_occupancy(
    kernel::shared_memory_size_determiner_t  shared_memory_size_determiner,
    cuda::grid::block_dimension_t            block_size_limit,
    bool                                     disable_caching_override) const
{
    memory::shared::size_t no_fixed_dynamic_shared_memory_size{ 0 };
    return kernel::occupancy::detail_::min_grid_params_for_max_occupancy(
        handle(), device_id(), shared_memory_size_determiner,
        no_fixed_dynamic_shared_memory_size, block_size_limit, disable_caching_override);
}
#endif // CUDA_VERSION >= 10000

inline grid::dimension_t kernel_t::max_active_blocks_per_multiprocessor(
    grid::block_dimension_t  block_size_in_threads,
    memory::shared::size_t   dynamic_shared_memory_per_block,
    bool                     disable_caching_override) const
{
    return kernel::occupancy::detail_::max_active_blocks_per_multiprocessor(
        handle(), block_size_in_threads,
        dynamic_shared_memory_per_block, disable_caching_override);
}

} // namespace cuda

#endif // CUDA_API_WRAPPERS_KERNEL_HPP_