llama-cpp-sys-4 0.7.0

Low Level Bindings to llama.cpp
Documentation
#version 450

#extension GL_EXT_control_flow_attributes : require
#extension GL_EXT_shader_16bit_storage : require
#extension GL_EXT_shader_explicit_arithmetic_types_float16 : require
#extension GL_KHR_shader_subgroup_basic : enable
#if USE_SUBGROUP_ADD
#extension GL_KHR_shader_subgroup_arithmetic : enable
#endif

#define BINDING_IDX_K 0u

#include "types.glsl"
#include "fa_types.glsl"
#define FaTypeV FA_TYPE_F32

layout(constant_id = 0) const uint FaTypeK = FA_TYPE_F32;
layout(constant_id = 1) const uint FaBlockBytesK = 4;
layout(constant_id = 2) const uint SUBGROUP_SIZE = 32;

#include "flash_attn_dequant.glsl"

// one workgroup computes one output element, one invocation per head element
#define HEAD_SIZE 128

layout(local_size_x = HEAD_SIZE, local_size_y = 1, local_size_z = 1) in;

layout(binding = 0) readonly buffer QBuf { float q[]; };
layout(binding = 1) readonly buffer KBufF16 { float16_t k_f16[]; };
layout(binding = 1) readonly buffer KBufF32 { float k_f32[]; };
layout(binding = 1) readonly buffer KBufBF16 { uint16_t k_bf16[]; };
layout(binding = 2) readonly buffer WBuf { float weights[]; };
layout(binding = 3) readonly buffer MBuf { float16_t mask[]; };
layout(binding = 4) writeonly buffer DstBuf { float dst[]; };

layout(push_constant) uniform PushConstants {
    uint n_kv;
    uint n_heads;
    uint n_tokens;
    uint n_streams;
    uint n_masks;
    uint dispatch_x;
    uint q_nb1;
    uint q_nb2;
    uint q_nb3;
    uint k_nb2;
    uint k_nb3;
    uint w_nb1;
    uint w_nb3;
    uint m_nb1;
    uint m_nb3;
    uint d_nb1;
    uint d_nb3;
};

shared float k_row[HEAD_SIZE];

#if USE_SUBGROUP_ADD
shared float sg_partials[HEAD_SIZE / SUBGROUP_SIZE];
#else
shared float partials[HEAD_SIZE];
#endif

void main() {
    const uint tid = gl_LocalInvocationID.x;
    const uint output_idx = gl_WorkGroupID.y * dispatch_x + gl_WorkGroupID.x;
    const uint n_outputs = n_kv * n_tokens * n_streams;

    if (fa_type_needs_shmem(FaTypeK)) {
        init_iq_shmem(gl_WorkGroupSize);
    }

    if (output_idx >= n_outputs) {
        return;
    }

    const uint ik = output_idx % n_kv;
    const uint ts = output_idx / n_kv;
    const uint t = ts % n_tokens;
    const uint s = ts / n_tokens;
    const uint k_offset = ik * k_nb2 + s * k_nb3;

    // k strides come in as bytes, so scale them down to the view being indexed
    const uint k_block_elems = fa_block_elems(FaTypeK);
    const uint k_elem_bytes = FaBlockBytesK / k_block_elems;

    if (FaTypeK == FA_TYPE_F16) {
        k_row[tid] = float(k_f16[k_offset / k_elem_bytes + tid]);
    } else if (FaTypeK == FA_TYPE_F32) {
        k_row[tid] = k_f32[k_offset / k_elem_bytes + tid];
    } else if (FaTypeK == FA_TYPE_BF16) {
        k_row[tid] = bf16_to_fp32(uint(k_bf16[k_offset / k_elem_bytes + tid]));
    } else if (4 * tid < HEAD_SIZE) {
        const uint coord = 4 * tid;
        const uint ib = coord / k_block_elems;
        const uint iqs = coord % k_block_elems;
        const vec4 values = dequantize4(ib, iqs, k_offset / FaBlockBytesK, BINDING_IDX_K);
        k_row[coord + 0] = values.x;
        k_row[coord + 1] = values.y;
        k_row[coord + 2] = values.z;
        k_row[coord + 3] = values.w;
    }
    barrier();

    const float k_val = k_row[tid];

    float score = 0.0;
    for (uint h = 0; h < n_heads; ++h) {
        const float prod = q[h * q_nb1 + t * q_nb2 + s * q_nb3 + tid] * k_val;

#if USE_SUBGROUP_ADD
        const float sg_sum = subgroupAdd(prod);
        if (gl_SubgroupInvocationID == 0) {
            sg_partials[gl_SubgroupID] = sg_sum;
        }
        barrier();

        if (tid == 0) {
            float sum = 0.0;
            [[unroll]] for (uint i = 0; i < HEAD_SIZE / SUBGROUP_SIZE; ++i) {
                sum += sg_partials[i];
            }
            score += max(sum, 0.0) * weights[h + t * w_nb1 + s * w_nb3];
        }
        // the reads above must complete before the next iteration overwrites sg_partials
        barrier();
#else
        partials[tid] = prod;
        barrier();

        [[unroll]] for (uint stride = HEAD_SIZE / 2; stride > 0; stride >>= 1) {
            if (tid < stride) {
                partials[tid] += partials[tid + stride];
            }
            barrier();
        }

        if (tid == 0) {
            score += max(partials[0], 0.0) * weights[h + t * w_nb1 + s * w_nb3];
        }
        // the read of partials[0] above must complete before the next iteration
        // overwrites partials[tid]
        barrier();
#endif
    }

    if (tid == 0) {
        const uint mask_offset = ik + t * m_nb1 + (s % n_masks) * m_nb3;
        dst[ik + t * d_nb1 + s * d_nb3] = score + float(mask[mask_offset]);
    }
}