ggml : add Vulkan backend (#2059)

* Vulkan loader code

* Fix matmul kernel, continue implementation

* Continue implementation

* Vulkan memory management

* Vulkan development

* Matmul call

* Add aligned malloc and free for VMA

* Continue implementation

* First matmul success

* GEMM Kernel optimization

* 1D Blocktiling

* 2D Blocktiling

* Write coalescing

* Continue vulkan implementation and optimization

* First FP16 attempt, disabled for now

* Code abstraction, FP16 implementation, fix kernel, add FP16 to FP32 kernel

* Enable device extensions properly, restore fp16 matmul op

* Fix mulmat_f16

* Output FP32 in fp16 matmul shader

* Fix f16_to_f32 kernel

* dequant_q4_0 kernel

* Add VMA library

* Avoid requesting dedicated memory, VMA can decide that by itself

* Add bounds checking to matmul kernels, improve implementation, fix command buffers not freed properly

* add cmake commands

* Add 2d write operation, profiling code

* Fix 2d write

* Fix queue selection for AMD RADV

* Fix trailing whitespace in vk_mem_alloc.h

* Add WIP warp tile mat mul shaders

* Disable glslc optimization

* Disable glslc optimization for CMake

* Optimize warptile matmul shader, replace blocktile with it

* Add split-k optimization for small matrix multiplication

Use semaphores for synchronization instead of fences or waitidle

Rework async write/read for synchronization

* Fix validation errors, improve compatibility with AMD GPUs

* Rework command buffer handling

* Variable matmul kernel using specialization constants

* Fix synchronization on AMD, add barriers for buffer ownership transfer, add debug flag and prints

* Reuse semaphores

* Handle stage flags during command buffer submission properly

* Increase matmul test runs for consistent results

* Fix F32 matmul

* Add vectorized loading and zeropadding for matrix multiplication

* Use pinned memory for f16 preprocessing

* Don't force aligned matmul

* Don't free before queue done

* Replace VMA library with native Vulkan buffer management

* Basic offloading support with mul_f32 and dmmv for q4_0

* Run glslc commands in parallel

* Unroll loops in dmmv shader

* Reduce usage of waitIdle

* Reuse pinned allocation for f16 conversion

* Handle devices with only a single queue

* Fix trailing whitespace in CMakeLists.txt

* Allow parallel execution of kernels, parallelize third and fourth dimension calls

* Add fallback for devices only supporting one DescriptorSet per DescriptorPool

* Move to graph function similar to CUDA implementation

* Use F16 kernel for most things, replace q_f32 with mul_mat_q_f16 function

* Add F32 dmmv shaders

* Batch submissions

* Add .spv to gitignore

* Split off matrix vector multiplication for separate optimization

* Use single command buffer for matrix vector multiplication ops

* Reduce overhead of mul_f32 calls by using a single command buffer

* Add submission batching to mul_f32

* Fix tests

* Add missing barrier

* Add further missing barrier

* Add further ops

* Replace vk::QueueFamilyIgnored with VK_QUEUE_FAMILY_IGNORED to support more Vulkan header versions

* Remove unnecessary cblas link

* Fix descriptor set pre-allocation assert

* Add runtime shader compilation, start transferring shaders to this approach

* Transfer remaining shaders to header and compile on runtime

* Fix fp32 fallback if device doesn't support fp16, add force disable env var GGML_VULKAN_DISABLE_F16

* Add support for q4_1, q5_0, q5_1 and q8_0

* Remove unnecessary scalar layout extension

* Parse graph early to pre-record command buffers

* Add q6_k support

* Add multi-submit for command buffers

* Fix q6_k dequant shader for AMD

* Fix q6_k for GPUs without fp16 support

* Simplify q6_k fp16 fix

* Minor fixes

* Fix wg_denom of m-mulmat shaders

* Add Python-based Vulkan shader generator

* Replace shaderc dependency with precompiled shaders

Fix python script to generate shaders

* Clean up code

* Fix shader generator script Windows compatibility

Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com>

* Close file before deletion

* Fix vulkan shader fp32 name

* Add q2_k and q3_k support

Add validation check to compare shader results to cpu results

* Add q4_k support

* Add q5_k support

* Bake SPIR-V bytecode into the library instead of loading shaders from file

* Switch to signal semaphores for flexibility

Prepare broadcasting support for mul mat

* Finish broadcasting mul mat support for GQA

* Clean up unused functions

Add repeat op

* Add further ops, not yet enabled. Improve semaphore code

* Reduce number of used semaphores by utilizing timelines more properly

* Remove queue information

* Reuse timeline semaphores, allow parallel operation with binary semaphores to work around nvidia driver limitations

* Add Vulkan to llama-bench

* Remove cblas dependency

* Fix matmul k-split bug

* Fix q4_k dmmv K_QUANTS_PER_ITERATION 1 shader

* Add RMS Norm shader, rework op_f32 shader setup, fix matmul bug

* Fix issues with float16 overflows in shaders

* Fix issues with older Vulkan headers on Ubuntu 22.04

* Allow multi-op partial offloading by parsing the graph to preallocate enough between-op buffers

* Implement further ops, rework op_f32 calls, fix bugs

* Finish full offloading support, add last remaining ops, fix bugs, remove redundant code

* Upload generated file ggml-vulkan-shaders.hpp, remove redundant shaders

* Merge upstream changes, fix conflicts, adapt soft_max op

* Fix Python and shader header format

* Free model gpu buffers on exit

* Use single queue per device to simplify code

* Add matmul shader support for running multiple calculations in parallel

* Switch from semaphore-synchronized multiple command buffers per op to single command buffer for multiple ops, whole graph if possible

* Fix missing event cast

* Replace uint64_t(-1) with UINT64_MAX, rename function for clarity

* Fix warning about empty C function parameters

* Fix compiler warnings

* Properly implement Vulkan backend buffer handling

* Fix oversized host staging buffers

* Simplify barrier synchronization calls

* Fix gcc warnings

* Implement max_size for backend buffer types to limit the size of a single allocation

* Use min of maxMemoryAllocationSize and maxBufferSize for device max allocation size

* refactor multi buf

* Disable unsupported ops to fix tests

* Check for maintenance4 support before using it

* Handle devices with only a single queue

* Fix single queue logic

* propagate buffer usage in multi buffers

* Implement rope_neox op

* Cleanup header and other files

* Simplify gpu_extras by removing events and putting staging memcpys into contexts

* Move queue into context

Add not-yet-enabled async backend ops

* Simplify context use, optimize matmul shader for warp size 64 (AMD GCN), fix split_k matmul shader optimization

* Add get_max_size to SYCL backend.

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* llama : fix trailing whitespace

---------

Co-authored-by: Henri Vasserman <henv@hot.ee>
Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com>
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

1 files changed, 102 insertions, 2 deletions

diff --git a/ggml-backend.c b/ggml-backend.c
index 897a4cb5..8b6cf7c9 100644
--- a/ggml-backend.c
+++ b/ggml-backend.c
@@ -27,6 +27,14 @@ size_t ggml_backend_buft_get_alignment(ggml_backend_buffer_type_t buft) {
     return buft->iface.get_alignment(buft);
 }
 
+size_t ggml_backend_buft_get_max_size(ggml_backend_buffer_type_t buft) {
+    // get_max_size is optional, defaults to SIZE_MAX
+    if (buft->iface.get_max_size) {
+        return buft->iface.get_max_size(buft);
+    }
+    return SIZE_MAX;
+}
+
 GGML_CALL size_t ggml_backend_buft_get_alloc_size(ggml_backend_buffer_type_t buft, struct ggml_tensor * tensor) {
     // get_alloc_size is optional, defaults to ggml_nbytes
     if (buft->iface.get_alloc_size) {
@@ -57,8 +65,6 @@ GGML_CALL ggml_backend_buffer_t ggml_backend_buffer_init(
                size_t                          size) {
     ggml_backend_buffer_t buffer = malloc(sizeof(struct ggml_backend_buffer));
 
-    GGML_ASSERT(iface.get_base != NULL);
-
     (*buffer) = (struct ggml_backend_buffer) {
         /* .interface = */ iface,
         /* .buft      = */ buft,
@@ -108,6 +114,10 @@ size_t ggml_backend_buffer_get_alignment (ggml_backend_buffer_t buffer) {
     return ggml_backend_buft_get_alignment(ggml_backend_buffer_get_type(buffer));
 }
 
+size_t ggml_backend_buffer_get_max_size(ggml_backend_buffer_t buffer) {
+    return ggml_backend_buft_get_max_size(ggml_backend_buffer_get_type(buffer));
+}
+
 size_t ggml_backend_buffer_get_alloc_size(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) {
     return ggml_backend_buft_get_alloc_size(ggml_backend_buffer_get_type(buffer), tensor);
 }
@@ -122,6 +132,11 @@ bool ggml_backend_buffer_is_host(ggml_backend_buffer_t buffer) {
 
 void ggml_backend_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage) {
     buffer->usage = usage;
+
+    // FIXME: add a generic callback to the buffer interface
+    if (ggml_backend_buffer_is_multi_buffer(buffer)) {
+        ggml_backend_multi_buffer_set_usage(buffer, usage);
+    }
 }
 
 ggml_backend_buffer_type_t ggml_backend_buffer_get_type(ggml_backend_buffer_t buffer) {
@@ -171,6 +186,10 @@ size_t ggml_backend_get_alignment(ggml_backend_t backend) {
     return ggml_backend_buft_get_alignment(ggml_backend_get_default_buffer_type(backend));
 }
 
+size_t ggml_backend_get_max_size(ggml_backend_t backend) {
+    return ggml_backend_buft_get_max_size(ggml_backend_get_default_buffer_type(backend));
+}
+
 void ggml_backend_tensor_set_async(ggml_backend_t backend, struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
     GGML_ASSERT(tensor->data != NULL && "tensor not allocated");
     GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor write out of bounds");
@@ -349,6 +368,11 @@ GGML_CALL static void ggml_backend_registry_init(void) {
     extern GGML_CALL ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void);
     ggml_backend_register("Metal", ggml_backend_reg_metal_init, ggml_backend_metal_buffer_type(), NULL);
 #endif
+
+#ifdef GGML_USE_VULKAN
+    extern GGML_CALL int ggml_backend_vk_reg_devices(void);
+    ggml_backend_vk_reg_devices();
+#endif
 }
 
 GGML_CALL void ggml_backend_register(const char * name, ggml_backend_init_fn init_fn, ggml_backend_buffer_type_t default_buffer_type, void * user_data) {
@@ -552,6 +576,7 @@ GGML_CALL ggml_backend_buffer_type_t ggml_backend_cpu_buffer_type(void) {
             /* .get_name         = */ ggml_backend_cpu_buffer_type_get_name,
             /* .alloc_buffer     = */ ggml_backend_cpu_buffer_type_alloc_buffer,
             /* .get_alignment    = */ ggml_backend_cpu_buffer_type_get_alignment,
+            /* .get_max_size     = */ NULL, // defaults to SIZE_MAX
             /* .get_alloc_size   = */ NULL, // defaults to ggml_nbytes
             /* .supports_backend = */ ggml_backend_cpu_buffer_type_supports_backend,
             /* .is_host          = */ ggml_backend_cpu_buffer_type_is_host,
@@ -607,6 +632,7 @@ ggml_backend_buffer_type_t ggml_backend_cpu_hbm_buffer_type(void) {
             /* .get_name         = */ ggml_backend_cpu_hbm_buffer_type_get_name,
             /* .alloc_buffer     = */ ggml_backend_cpu_hbm_buffer_type_alloc_buffer,
             /* .get_alignment    = */ ggml_backend_cpu_buffer_type_get_alignment,
+            /* .get_max_size     = */ NULL, // defaults to SIZE_MAX
             /* .get_alloc_size   = */ NULL, // defaults to ggml_nbytes
             /* .supports_backend = */ ggml_backend_cpu_buffer_type_supports_backend,
             /* .is_host          = */ ggml_backend_cpu_buffer_type_is_host,
@@ -763,6 +789,80 @@ GGML_CALL static ggml_backend_t ggml_backend_reg_cpu_init(const char * params, v
     GGML_UNUSED(user_data);
 }
 
+// multi-buffer buffer
+
+struct ggml_backend_multi_buffer_context {
+    ggml_backend_buffer_t * buffers;
+    size_t n_buffers;
+};
+
+typedef struct ggml_backend_multi_buffer_context * ggml_backend_multi_buffer_context_t;
+
+GGML_CALL static const char * ggml_backend_multi_buffer_get_name(ggml_backend_buffer_t buffer) {
+    ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) buffer->context;
+
+    return ctx->buffers[0]->iface.get_name(ctx->buffers[0]);
+}
+
+GGML_CALL static void ggml_backend_multi_buffer_free_buffer(ggml_backend_buffer_t buffer) {
+    ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) buffer->context;
+    for (size_t i = 0; i < ctx->n_buffers; i++) {
+        ggml_backend_buffer_free(ctx->buffers[i]);
+    }
+
+    free(ctx->buffers);
+    free(ctx);
+}
+
+GGML_CALL static void ggml_backend_multi_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) {
+    ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) buffer->context;
+    for (size_t i = 0; i < ctx->n_buffers; i++) {
+        ggml_backend_buffer_clear(ctx->buffers[i], value);
+    }
+}
+
+static struct ggml_backend_buffer_i ggml_backend_multi_buffer_context_interface(void) {
+    static struct ggml_backend_buffer_i multi_backend_buffer_i = {
+        /* .get_name        = */ ggml_backend_multi_buffer_get_name,
+        /* .free_buffer     = */ ggml_backend_multi_buffer_free_buffer,
+        /* .get_base        = */ NULL,
+        /* .init_tensor     = */ NULL,
+        /* .set_tensor      = */ NULL,
+        /* .get_tensor      = */ NULL,
+        /* .cpy_tensor      = */ NULL,
+        /* .clear           = */ ggml_backend_multi_buffer_clear,
+        /* .reset           = */ NULL,
+    };
+
+    return multi_backend_buffer_i;
+}
+
+GGML_CALL ggml_backend_buffer_t ggml_backend_multi_buffer_alloc_buffer(ggml_backend_buffer_t * buffers, size_t n_buffers) {
+    ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) malloc(sizeof(struct ggml_backend_multi_buffer_context));
+    ctx->n_buffers = n_buffers;
+    ctx->buffers = (ggml_backend_buffer_t *) malloc(n_buffers * sizeof(ggml_backend_buffer_t));
+
+    size_t total_size = 0;
+    for (size_t i = 0; i < n_buffers; i++) {
+        ctx->buffers[i] = buffers[i];
+        total_size += ggml_backend_buffer_get_size(buffers[i]);
+    }
+
+    return ggml_backend_buffer_init(buffers[0]->buft, ggml_backend_multi_buffer_context_interface(), ctx, total_size);
+}
+
+GGML_CALL bool ggml_backend_buffer_is_multi_buffer(ggml_backend_buffer_t buffer) {
+    return buffer->iface.get_name == ggml_backend_multi_buffer_get_name;
+}
+
+GGML_CALL void ggml_backend_multi_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage) {
+    GGML_ASSERT(ggml_backend_buffer_is_multi_buffer(buffer));
+    ggml_backend_multi_buffer_context_t ctx = (ggml_backend_multi_buffer_context_t) buffer->context;
+    for (size_t i = 0; i < ctx->n_buffers; i++) {
+        ggml_backend_buffer_set_usage(ctx->buffers[i], usage);
+    }
+}
+
 
 // scheduler