metal : fix memory leak (#2762)

* metal : fix memory leak

* metal : fix encoders memory leak

* metal : clean up more memory resources

* metal : fix more leaks

* metal : reuse dispatch queue + autoreleasepool

* metal : reuse array for command buffers and encoders

* ggml : assert for odd number of blocks on ARM

15M tinyllama is an example
This commit is contained in:
Georgi Gerganov 2023-08-28 10:59:08 +03:00 committed by GitHub
parent ebcee207b6
commit f55538c3cc
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 88 additions and 24 deletions

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@ -24,6 +24,7 @@
// max memory buffers that can be mapped to the device
#define GGML_METAL_MAX_BUFFERS 16
#define GGML_METAL_MAX_COMMAND_BUFFERS 32
struct ggml_tensor;
struct ggml_cgraph;

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@ -33,12 +33,15 @@ struct ggml_metal_buffer {
struct ggml_metal_context {
int n_cb;
float * logits;
id<MTLDevice> device;
id<MTLCommandQueue> queue;
id<MTLLibrary> library;
id<MTLCommandBuffer> command_buffers [GGML_METAL_MAX_COMMAND_BUFFERS];
id<MTLComputeCommandEncoder> command_encoders[GGML_METAL_MAX_COMMAND_BUFFERS];
dispatch_queue_t d_queue;
int n_buffers;
struct ggml_metal_buffer buffers[GGML_METAL_MAX_BUFFERS];
@ -114,12 +117,13 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
struct ggml_metal_context * ctx = malloc(sizeof(struct ggml_metal_context));
ctx->n_cb = n_cb;
ctx->n_cb = MIN(n_cb, GGML_METAL_MAX_BUFFERS);
ctx->device = MTLCreateSystemDefaultDevice();
ctx->queue = [ctx->device newCommandQueue];
ctx->n_buffers = 0;
ctx->concur_list_len = 0;
ctx->d_queue = dispatch_queue_create("llama.cpp", DISPATCH_QUEUE_CONCURRENT);
#if 0
// compile from source string and show compile log
@ -239,9 +243,67 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
void ggml_metal_free(struct ggml_metal_context * ctx) {
fprintf(stderr, "%s: deallocating\n", __func__);
#define GGML_METAL_DEL_KERNEL(name) \
[ctx->function_##name release]; \
[ctx->pipeline_##name release];
GGML_METAL_DEL_KERNEL(add);
GGML_METAL_DEL_KERNEL(add_row);
GGML_METAL_DEL_KERNEL(mul);
GGML_METAL_DEL_KERNEL(mul_row);
GGML_METAL_DEL_KERNEL(scale);
GGML_METAL_DEL_KERNEL(silu);
GGML_METAL_DEL_KERNEL(relu);
GGML_METAL_DEL_KERNEL(gelu);
GGML_METAL_DEL_KERNEL(soft_max);
GGML_METAL_DEL_KERNEL(diag_mask_inf);
GGML_METAL_DEL_KERNEL(get_rows_f16);
GGML_METAL_DEL_KERNEL(get_rows_q4_0);
GGML_METAL_DEL_KERNEL(get_rows_q4_1);
GGML_METAL_DEL_KERNEL(get_rows_q8_0);
GGML_METAL_DEL_KERNEL(get_rows_q2_K);
GGML_METAL_DEL_KERNEL(get_rows_q3_K);
GGML_METAL_DEL_KERNEL(get_rows_q4_K);
GGML_METAL_DEL_KERNEL(get_rows_q5_K);
GGML_METAL_DEL_KERNEL(get_rows_q6_K);
GGML_METAL_DEL_KERNEL(rms_norm);
GGML_METAL_DEL_KERNEL(norm);
GGML_METAL_DEL_KERNEL(mul_mat_f16_f32);
GGML_METAL_DEL_KERNEL(mul_mat_q4_0_f32);
GGML_METAL_DEL_KERNEL(mul_mat_q4_1_f32);
GGML_METAL_DEL_KERNEL(mul_mat_q8_0_f32);
GGML_METAL_DEL_KERNEL(mul_mat_q2_K_f32);
GGML_METAL_DEL_KERNEL(mul_mat_q3_K_f32);
GGML_METAL_DEL_KERNEL(mul_mat_q4_K_f32);
GGML_METAL_DEL_KERNEL(mul_mat_q5_K_f32);
GGML_METAL_DEL_KERNEL(mul_mat_q6_K_f32);
GGML_METAL_DEL_KERNEL(mul_mm_f16_f32);
GGML_METAL_DEL_KERNEL(mul_mm_q4_0_f32);
GGML_METAL_DEL_KERNEL(mul_mm_q8_0_f32);
GGML_METAL_DEL_KERNEL(mul_mm_q4_1_f32);
GGML_METAL_DEL_KERNEL(mul_mm_q2_K_f32);
GGML_METAL_DEL_KERNEL(mul_mm_q3_K_f32);
GGML_METAL_DEL_KERNEL(mul_mm_q4_K_f32);
GGML_METAL_DEL_KERNEL(mul_mm_q5_K_f32);
GGML_METAL_DEL_KERNEL(mul_mm_q6_K_f32);
GGML_METAL_DEL_KERNEL(rope);
GGML_METAL_DEL_KERNEL(alibi_f32);
GGML_METAL_DEL_KERNEL(cpy_f32_f16);
GGML_METAL_DEL_KERNEL(cpy_f32_f32);
GGML_METAL_DEL_KERNEL(cpy_f16_f16);
#undef GGML_METAL_DEL_KERNEL
for (int i = 0; i < ctx->n_buffers; ++i) {
[ctx->buffers[i].metal release];
}
[ctx->library release];
[ctx->queue release];
[ctx->device release];
dispatch_release(ctx->d_queue);
free(ctx);
}
@ -261,7 +323,7 @@ void ggml_metal_host_free(void * data) {
}
void ggml_metal_set_n_cb(struct ggml_metal_context * ctx, int n_cb) {
ctx->n_cb = n_cb;
ctx->n_cb = MIN(n_cb, GGML_METAL_MAX_BUFFERS);
}
int ggml_metal_if_optimized(struct ggml_metal_context * ctx) {
@ -507,6 +569,8 @@ void ggml_metal_graph_compute(
struct ggml_cgraph * gf) {
metal_printf("%s: evaluating graph\n", __func__);
@autoreleasepool {
// if there is ctx->concur_list, dispatch concurrently
// else fallback to serial dispatch
MTLComputePassDescriptor * edesc = MTLComputePassDescriptor.computePassDescriptor;
@ -521,29 +585,25 @@ void ggml_metal_graph_compute(
const int n_cb = ctx->n_cb;
NSMutableArray * command_buffers = [NSMutableArray arrayWithCapacity:n_cb];
for (int i = 0; i < n_cb; ++i) {
command_buffers[i] = [ctx->queue commandBuffer];
ctx->command_buffers[i] = [ctx->queue commandBuffer];
// enqueue the command buffers in order to specify their execution order
[command_buffers[i] enqueue];
}
[ctx->command_buffers[i] enqueue];
// TODO: is this the best way to start threads?
dispatch_queue_t queue = dispatch_queue_create("llama.cpp", DISPATCH_QUEUE_CONCURRENT);
ctx->command_encoders[i] = [ctx->command_buffers[i] computeCommandEncoderWithDescriptor: edesc];
}
for (int cb_idx = 0; cb_idx < n_cb; ++cb_idx) {
const int n_nodes_per_cb = (n_nodes + n_cb - 1) / n_cb;
dispatch_async(queue, ^{
dispatch_async(ctx->d_queue, ^{
size_t offs_src0 = 0;
size_t offs_src1 = 0;
size_t offs_dst = 0;
id<MTLCommandBuffer> command_buffer = command_buffers[cb_idx];
id<MTLComputeCommandEncoder> encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
id<MTLCommandBuffer> command_buffer = ctx->command_buffers[cb_idx];
id<MTLComputeCommandEncoder> encoder = ctx->command_encoders[cb_idx];
const int node_start = (cb_idx + 0) * n_nodes_per_cb;
const int node_end = MIN((cb_idx == n_cb - 1) ? n_nodes : (cb_idx + 1) * n_nodes_per_cb, n_nodes);
@ -1117,17 +1177,19 @@ void ggml_metal_graph_compute(
}
// wait for all threads to finish
dispatch_barrier_sync(queue, ^{});
[command_buffers[n_cb - 1] waitUntilCompleted];
dispatch_barrier_sync(ctx->d_queue, ^{});
// check status of command buffers
// needed to detect if the device ran out-of-memory for example (#1881)
for (int i = 0; i < n_cb; i++) {
MTLCommandBufferStatus status = (MTLCommandBufferStatus) [command_buffers[i] status];
[ctx->command_buffers[i] waitUntilCompleted];
MTLCommandBufferStatus status = (MTLCommandBufferStatus) [ctx->command_buffers[i] status];
if (status != MTLCommandBufferStatusCompleted) {
fprintf(stderr, "%s: command buffer %d failed with status %lu\n", __func__, i, status);
GGML_ASSERT(false);
}
}
}
}

11
ggml.c
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@ -2436,7 +2436,6 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
const int nb = n / qk;
assert(n % qk == 0);
assert(nb % 2 == 0);
const block_q4_0 * restrict x = vx;
const block_q8_0 * restrict y = vy;
@ -2445,6 +2444,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
float32x4_t sumv0 = vdupq_n_f32(0.0f);
float32x4_t sumv1 = vdupq_n_f32(0.0f);
GGML_ASSERT(nb % 2 == 0); // TODO: handle odd nb
for (int i = 0; i < nb; i += 2) {
const block_q4_0 * restrict x0 = &x[i + 0];
const block_q4_0 * restrict x1 = &x[i + 1];
@ -2623,6 +2623,7 @@ static void ggml_vec_dot_q4_0_q8_0(const int n, float * restrict s, const void *
}
// Main loop
GGML_ASSERT(nb % 2 == 0); // TODO: handle odd nb
for (int i = 2; i < nb; i+=2) {
_mm_prefetch(&x[i] + sizeof(block_q4_0), _MM_HINT_T0);
_mm_prefetch(&y[i] + sizeof(block_q8_0), _MM_HINT_T0);
@ -2706,7 +2707,6 @@ static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void *
const int nb = n / qk;
assert(n % qk == 0);
assert(nb % 2 == 0);
const block_q4_1 * restrict x = vx;
const block_q8_1 * restrict y = vy;
@ -2718,6 +2718,7 @@ static void ggml_vec_dot_q4_1_q8_1(const int n, float * restrict s, const void *
float summs = 0;
GGML_ASSERT(nb % 2 == 0); // TODO: handle odd nb
for (int i = 0; i < nb; i += 2) {
const block_q4_1 * restrict x0 = &x[i + 0];
const block_q4_1 * restrict x1 = &x[i + 1];
@ -2832,7 +2833,6 @@ static void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void *
const int nb = n / qk;
assert(n % qk == 0);
assert(nb % 2 == 0);
assert(qk == QK5_0);
const block_q5_0 * restrict x = vx;
@ -2848,6 +2848,7 @@ static void ggml_vec_dot_q5_0_q8_0(const int n, float * restrict s, const void *
uint64_t tmp0[4];
uint64_t tmp1[4];
GGML_ASSERT(nb % 2 == 0); // TODO: handle odd nb
for (int i = 0; i < nb; i += 2) {
const block_q5_0 * restrict x0 = &x[i];
const block_q5_0 * restrict x1 = &x[i + 1];
@ -3072,7 +3073,6 @@ static void ggml_vec_dot_q5_1_q8_1(const int n, float * restrict s, const void *
const int nb = n / qk;
assert(n % qk == 0);
assert(nb % 2 == 0);
assert(qk == QK5_1);
const block_q5_1 * restrict x = vx;
@ -3091,6 +3091,7 @@ static void ggml_vec_dot_q5_1_q8_1(const int n, float * restrict s, const void *
uint64_t tmp0[4];
uint64_t tmp1[4];
GGML_ASSERT(nb % 2 == 0); // TODO: handle odd nb
for (int i = 0; i < nb; i += 2) {
const block_q5_1 * restrict x0 = &x[i];
const block_q5_1 * restrict x1 = &x[i + 1];
@ -3328,7 +3329,6 @@ static void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void *
const int nb = n / qk;
assert(n % qk == 0);
assert(nb % 2 == 0);
const block_q8_0 * restrict x = vx;
const block_q8_0 * restrict y = vy;
@ -3337,6 +3337,7 @@ static void ggml_vec_dot_q8_0_q8_0(const int n, float * restrict s, const void *
float32x4_t sumv0 = vdupq_n_f32(0.0f);
float32x4_t sumv1 = vdupq_n_f32(0.0f);
GGML_ASSERT(nb % 2 == 0); // TODO: handle odd nb
for (int i = 0; i < nb; i += 2) {
const block_q8_0 * restrict x0 = &x[i + 0];
const block_q8_0 * restrict x1 = &x[i + 1];