struct dnnl::ukernel::brgemm

Intel® oneAPI Deep Neural Network Developer Guide and Reference

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ID 768875

Date 9/17/2024

Version

Public

Visible to Intel only — GUID: GUID-A1EBC593-CEF5-40FE-BE85-D5B8786D4984

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struct dnnl::ukernel::brgemm

Overview

BRGeMM ukernel. More…

#include <dnnl_ukernel.hpp>

struct brgemm: public dnnl::handle
{
    // construction

    brgemm();

    brgemm(
        memory::dim M,
        memory::dim N,
        memory::dim K,
        memory::dim batch_size,
        memory::dim lda,
        memory::dim ldb,
        memory::dim ldc,
        memory::data_type a_dt,
        memory::data_type b_dt,
        memory::data_type c_dt,
        bool allow_empty = false
        );

    // methods

    void set_add_C(bool add_C);

    void set_post_ops(
        memory::dim ldd,
        memory::data_type d_dt,
        const post_ops& po = default_post_ops()
        );

    void set_A_scales(int a_scale_mask);
    void set_B_scales(int b_scale_mask);
    void set_D_scales(int d_scale_mask);
    void finalize();
    pack_type get_B_pack_type() const;
    size_t get_scratchpad_size() const;
    void set_hw_context() const;
    void generate();

    void execute(
        const void* A,
        const void* B,
        const std::vector<std::pair<memory::dim, memory::dim>>& A_B_offsets,
        void* C,
        void* scratchpad
        ) const;

    void execute(
        const void* A,
        const void* B,
        const std::vector<std::pair<memory::dim, memory::dim>>& A_B_offsets,
        void* C,
        void* D,
        void* scratchpad,
        const attr_params& params = default_attr_params()
        ) const;

    static void release_hw_context();
    static const post_ops& default_post_ops();
    static const attr_params& default_attr_params();
};

Inherited Members

public:
    // methods

    handle<T, traits>& operator = (const handle<T, traits>&);
    handle<T, traits>& operator = (handle<T, traits>&&);
    void reset(T t, bool weak = false);
    T get(bool allow_empty = false) const;
    operator T () const;
    operator bool () const;
    bool operator == (const handle<T, traits>& other) const;
    bool operator != (const handle& other) const;

Detailed Documentation

BRGeMM ukernel.

Construction

brgemm()

Default constructor. Produces an empty object.

brgemm(
    memory::dim M,
    memory::dim N,
    memory::dim K,
    memory::dim batch_size,
    memory::dim lda,
    memory::dim ldb,
    memory::dim ldc,
    memory::data_type a_dt,
    memory::data_type b_dt,
    memory::data_type c_dt,
    bool allow_empty = false
    )

Constructs a BRGeMM ukernel object.

Operates by the following formula: C = [A x B].

Parameters:

M	Dimension M of tensor A.
N	Dimension N of tensor B.
K	Dimension K of tensors A and B.
batch_size	Number of batches to process.
lda	Leading dimension of tensor A.
ldb	Leading dimension of tensor B.
ldc	Leading dimension of tensor C.
a_dt	Data type of tensor A.
b_dt	Data type of tensor B.
c_dt	Data type of tensor C.
allow_empty	A flag signifying whether construction is allowed to fail without throwing an exception. In this case an empty object will be produced. This flag is optional and defaults to false.

Methods

void set_add_C(bool add_C)

Sets adding an intermediate result to the output tensor C instead of writing: C += [A x B].

Parameters:

add_C

Value to indicate addition. false to skip addition, and true to apply addition.

void set_post_ops(
    memory::dim ldd,
    memory::data_type d_dt,
    const post_ops& po = default_post_ops()
    )

Sets post-operations to a BRGeMM ukernel object: D = post-operations(C).

Post-operations applies if one of the following holds:

Non-empty post-operations are specified.
Output data type d_dt is different from accumulation data type c_dt.

Parameters:

ldd	Leading dimension of tensor D.
d_dt	Data type of tensor D.
po	Primitive post-operation attributes to extend the kernel operations.

void set_A_scales(int a_scale_mask)

Sets tensor A scales mask to a BRGeMM ukernel object.

For quantization flavor tensor A scales apply to accumulation buffer once C is ready.

Parameters:

a_scale_mask

Tensor A scale mask. Can be 0 only.

void set_B_scales(int b_scale_mask)

Sets tensor B scales mask to a BRGeMM ukernel object.

For quantization flavor tensor B scales apply to accumulation buffer once C is ready.

Parameters:

b_scale_mask

Tensor B scale mask. Can be 0 and 2 only.

void set_D_scales(int d_scale_mask)

Sets tensor D scales mask to a BRGeMM ukernel object.

For quantization flavor tensor D scales apply after all post-ops are applied.

Parameters:

d_scale_mask

Tensor D scale mask. Can be 0 only.

void finalize()

Finalizes initialization of a BRGeMM ukernel object.

This step must be performed prior to querying information from the object.

pack_type get_B_pack_type() const

Returns the packing type expected by a tensor B of a BRGeMM ukernel object.

size_t get_scratchpad_size() const

Returns the size of a scratchpad memory needed for the BRGeMM ukernel object.

void set_hw_context() const

Initializes the hardware-specific context.

Affects the global state for all BRGeMM ukernel objects. If no initialization required, returns.

void generate()

Generates an executable part of BRGeMM ukernel object.

void execute(
    const void* A,
    const void* B,
    const std::vector<std::pair<memory::dim, memory::dim>>& A_B_offsets,
    void* C,
    void* scratchpad
    ) const

Executes a BRGeMM ukernel object.

Parameters:

A	Base pointer to a tensor A.
B	Base pointer to a tensor B.
A_B_offsets	Vector of pairs of tensors A and B offsets for each batch. The number of batches must coincide with the `batch_size` value passed at object construction stage.
C	Pointer to a tensor C (accumulation buffer).
scratchpad	Pointer to a scratchpad buffer.

void execute(
    const void* A,
    const void* B,
    const std::vector<std::pair<memory::dim, memory::dim>>& A_B_offsets,
    void* C,
    void* D,
    void* scratchpad,
    const attr_params& params = default_attr_params()
    ) const

Executes a BRGeMM ukernel object with post operations.

Parameters:

A	Base pointer to a tensor A.
B	Base pointer to a tensor B.
A_B_offsets	Vector of pairs of tensors A and B offsets for each batch. The number of batches must coincide with the `batch_size` value passed at object construction stage.
C	Pointer to a tensor C (accumulation buffer).
D	Pointer to a tensor D (output buffer).
scratchpad	Pointer to a scratchpad buffer.
params	Post-op memory arguments. Must be passed If binary post-op or scales were set.

static void release_hw_context()

Releases the hardware-specific context.

Affects the global state for all BRGeMM ukernel objects. Must be used after all the execution calls to BRGeMM ukernel objects.

static const post_ops& default_post_ops()

Returns a constant reference to a static instance of default constructed primitive post-operations attribute.

static const attr_params& default_attr_params()

Returns a constant reference to a static instance of default constructed ukernel attributes parameters.

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Intel® oneAPI Deep Neural Network Developer Guide and Reference

struct dnnl::ukernel::brgemm

Overview

Detailed Documentation