vbatts/llama.cpp
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llama : ggml-backend integration (#4766)

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* llama : ggml-backend integration

* ggml-backend : add names to buffers

* fix unmap after loading

* batched-bench : add tensor_split param

* llama : check for null tensor_split

* ggml-backend : increase GGML_MAX_BACKENDS

* improve graph splitting, partial fix for --no-kv-offload

* cuda : add ggml-backend split buffer support

* cuda : do not create buffer types for devices that don't exist (fixes usage without CUDA devices available)

* ggml : fix null backend dereference (#4807)

* ggml : fix null backend dereference

* ggml : also check ggml_backend_is_cpu

* test-backend-ops : check buffer allocation failures

* llama : add cparam (split_mode) and command line argument (--split-mode, -sm) to configure the split mode (none, layer or row)

* ggml : fix mul_mat_id work size

* llama : rewrite session kv load/set without graphs

* minor

* llama : only initialize used backends, free backends on context free

* llama : abort ctx if cuda backend init fails

* llama : rewrite lora with ggml-backend and compute on CPU

ggml-ci

* llama : only map to a backend buffer the region of the file mapping containing the tensors used in the buffer

* opencl : add ggml-backend buffer type

* cuda : only use batched_cublas with batched mat muls (fixes fp16 tg perf)

* llama : on Metal, by default offload the full model

ggml-ci

* metal : page align the data ptr (#4854)

* Apply suggestions from code review

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* cuda : fix split buffer free

* address review comments

* llama-bench : add split-mode parameter

* fix whitespace

* opencl : fix double initialization

* server : add --split-mode parameter

* use async copy and compute to improve multi-gpu performance

ggml-ci

* use async memcpys to copy the graph outputs to the CPU

* fix opencl

* use a host buffer for the cpu compute buffer for faster copies to the gpu

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
This commit is contained in:
slaren 2024-01-12 20:07:38 +01:00 • committed by GitHub
parent 584d674be6
commit e7e4df031b
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21 changed files with 2533 additions and 2295 deletions
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146
examples/llama-bench/llama-bench.cpp
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@ -128,6 +128,25 @@ static std::string get_gpu_info() {
// command line params
enum output_formats {CSV, JSON, MARKDOWN, SQL};
static const char * output_format_str(output_formats format) {
switch (format) {
case CSV: return "csv";
case JSON: return "json";
case MARKDOWN: return "md";
case SQL: return "sql";
default: GGML_ASSERT(!"invalid output format");
}
}
static const char * split_mode_str(llama_split_mode mode) {
switch (mode) {
case LLAMA_SPLIT_NONE: return "none";
case LLAMA_SPLIT_LAYER: return "layer";
case LLAMA_SPLIT_ROW: return "row";
default: GGML_ASSERT(!"invalid split mode");
}
}
struct cmd_params {
std::vector<std::string> model;
std::vector<int> n_prompt;
@ -137,6 +156,7 @@ struct cmd_params {
std::vector<ggml_type> type_v;
std::vector<int> n_threads;
std::vector<int> n_gpu_layers;
std::vector<llama_split_mode> split_mode;
std::vector<int> main_gpu;
std::vector<bool> no_kv_offload;
std::vector<bool> mul_mat_q;
@ -155,6 +175,7 @@ static const cmd_params cmd_params_defaults = {
/* type_v */ {GGML_TYPE_F16},
/* n_threads */ {get_num_physical_cores()},
/* n_gpu_layers */ {99},
/* split_mode */ {LLAMA_SPLIT_LAYER},
/* main_gpu */ {0},
/* no_kv_offload */ {false},
/* mul_mat_q */ {true},
@ -169,21 +190,22 @@ static void print_usage(int /* argc */, char ** argv) {
printf("\n");
printf("options:\n");
printf(" -h, --help\n");
printf(" -m, --model <filename> (default: %s)\n", join(cmd_params_defaults.model, ",").c_str());
printf(" -p, --n-prompt <n> (default: %s)\n", join(cmd_params_defaults.n_prompt, ",").c_str());
printf(" -n, --n-gen <n> (default: %s)\n", join(cmd_params_defaults.n_gen, ",").c_str());
printf(" -b, --batch-size <n> (default: %s)\n", join(cmd_params_defaults.n_batch, ",").c_str());
printf(" -ctk <t>, --cache-type-k <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_k, ggml_type_name), ",").c_str());
printf(" -ctv <t>, --cache-type-v <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_v, ggml_type_name), ",").c_str());
printf(" -t, --threads <n> (default: %s)\n", join(cmd_params_defaults.n_threads, ",").c_str());
printf(" -ngl, --n-gpu-layers <n> (default: %s)\n", join(cmd_params_defaults.n_gpu_layers, ",").c_str());
printf(" -mg, --main-gpu <i> (default: %s)\n", join(cmd_params_defaults.main_gpu, ",").c_str());
printf(" -nkvo, --no-kv-offload <0|1> (default: %s)\n", join(cmd_params_defaults.no_kv_offload, ",").c_str());
printf(" -mmq, --mul-mat-q <0|1> (default: %s)\n", join(cmd_params_defaults.mul_mat_q, ",").c_str());
printf(" -ts, --tensor_split <ts0/ts1/..> \n");
printf(" -r, --repetitions <n> (default: %d)\n", cmd_params_defaults.reps);
printf(" -o, --output <csv|json|md|sql> (default: %s)\n", cmd_params_defaults.output_format == CSV ? "csv" : cmd_params_defaults.output_format == JSON ? "json" : cmd_params_defaults.output_format == MARKDOWN ? "md" : "sql");
printf(" -v, --verbose (default: %s)\n", cmd_params_defaults.verbose ? "1" : "0");
printf(" -m, --model <filename> (default: %s)\n", join(cmd_params_defaults.model, ",").c_str());
printf(" -p, --n-prompt <n> (default: %s)\n", join(cmd_params_defaults.n_prompt, ",").c_str());
printf(" -n, --n-gen <n> (default: %s)\n", join(cmd_params_defaults.n_gen, ",").c_str());
printf(" -b, --batch-size <n> (default: %s)\n", join(cmd_params_defaults.n_batch, ",").c_str());
printf(" -ctk <t>, --cache-type-k <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_k, ggml_type_name), ",").c_str());
printf(" -ctv <t>, --cache-type-v <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_v, ggml_type_name), ",").c_str());
printf(" -t, --threads <n> (default: %s)\n", join(cmd_params_defaults.n_threads, ",").c_str());
printf(" -ngl, --n-gpu-layers <n> (default: %s)\n", join(cmd_params_defaults.n_gpu_layers, ",").c_str());
printf(" -sm, --split-mode <none|layer|row> (default: %s)\n", join(transform_to_str(cmd_params_defaults.split_mode, split_mode_str), ",").c_str());
printf(" -mg, --main-gpu <i> (default: %s)\n", join(cmd_params_defaults.main_gpu, ",").c_str());
printf(" -nkvo, --no-kv-offload <0|1> (default: %s)\n", join(cmd_params_defaults.no_kv_offload, ",").c_str());
printf(" -mmq, --mul-mat-q <0|1> (default: %s)\n", join(cmd_params_defaults.mul_mat_q, ",").c_str());
printf(" -ts, --tensor_split <ts0/ts1/..> (default: 0)\n");
printf(" -r, --repetitions <n> (default: %d)\n", cmd_params_defaults.reps);
printf(" -o, --output <csv|json|md|sql> (default: %s)\n", output_format_str(cmd_params_defaults.output_format));
printf(" -v, --verbose (default: %s)\n", cmd_params_defaults.verbose ? "1" : "0");
printf("\n");
printf("Multiple values can be given for each parameter by separating them with ',' or by specifying the parameter multiple times.\n");
}
@ -306,6 +328,28 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
}
auto p = split<int>(argv[i], split_delim);
params.n_gpu_layers.insert(params.n_gpu_layers.end(), p.begin(), p.end());
} else if (arg == "-sm" || arg == "--split-mode") {
if (++i >= argc) {
invalid_param = true;
break;
}
auto p = split<std::string>(argv[i], split_delim);
std::vector<llama_split_mode> modes;
for (const auto & m : p) {
llama_split_mode mode;
if (m == "none") {
mode = LLAMA_SPLIT_NONE;
} else if (m == "layer") {
mode = LLAMA_SPLIT_LAYER;
} else if (m == "row") {
mode = LLAMA_SPLIT_ROW;
} else {
invalid_param = true;
break;
}
modes.push_back(mode);
}
params.split_mode.insert(params.split_mode.end(), modes.begin(), modes.end());
} else if (arg == "-mg" || arg == "--main-gpu") {
if (++i >= argc) {
invalid_param = true;
@ -392,6 +436,7 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
if (params.type_k.empty()) { params.type_k = cmd_params_defaults.type_k; }
if (params.type_v.empty()) { params.type_v = cmd_params_defaults.type_v; }
if (params.n_gpu_layers.empty()) { params.n_gpu_layers = cmd_params_defaults.n_gpu_layers; }
if (params.split_mode.empty()) { params.split_mode = cmd_params_defaults.split_mode; }
if (params.main_gpu.empty()) { params.main_gpu = cmd_params_defaults.main_gpu; }
if (params.no_kv_offload.empty()){ params.no_kv_offload = cmd_params_defaults.no_kv_offload; }
if (params.mul_mat_q.empty()) { params.mul_mat_q = cmd_params_defaults.mul_mat_q; }
@ -410,6 +455,7 @@ struct cmd_params_instance {
ggml_type type_v;
int n_threads;
int n_gpu_layers;
llama_split_mode split_mode;
int main_gpu;
bool no_kv_offload;
bool mul_mat_q;
@ -419,6 +465,7 @@ struct cmd_params_instance {
llama_model_params mparams = llama_model_default_params();
mparams.n_gpu_layers = n_gpu_layers;
mparams.split_mode = split_mode;
mparams.main_gpu = main_gpu;
mparams.tensor_split = tensor_split.data();
@ -428,6 +475,7 @@ struct cmd_params_instance {
bool equal_mparams(const cmd_params_instance & other) const {
return model == other.model &&
n_gpu_layers == other.n_gpu_layers &&
split_mode == other.split_mode &&
main_gpu == other.main_gpu &&
tensor_split == other.tensor_split;
}
@ -446,45 +494,13 @@ struct cmd_params_instance {
}
};
static std::vector<cmd_params_instance> get_cmd_params_instances_int(const cmd_params & params, int n_gen, int n_prompt) {
std::vector<cmd_params_instance> instances;
for (const auto & m : params.model)
for (const auto & nl : params.n_gpu_layers)
for (const auto & mg : params.main_gpu)
for (const auto & ts : params.tensor_split)
for (const auto & nb : params.n_batch)
for (const auto & tk : params.type_k)
for (const auto & tv : params.type_v)
for (const auto & mmq : params.mul_mat_q)
for (const auto & nkvo : params.no_kv_offload)
for (const auto & nt : params.n_threads) {
cmd_params_instance instance = {
/* .model = */ m,
/* .n_prompt = */ n_prompt,
/* .n_gen = */ n_gen,
/* .n_batch = */ nb,
/* .type_k = */ tk,
/* .type_v = */ tv,
/* .n_threads = */ nt,
/* .n_gpu_layers = */ nl,
/* .main_gpu = */ mg,
/* .no_kv_offload= */ nkvo,
/* .mul_mat_q = */ mmq,
/* .tensor_split = */ ts,
};
instances.push_back(instance);
}
return instances;
}
static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_params & params) {
std::vector<cmd_params_instance> instances;
#if 1
// this ordering minimizes the number of times that each model needs to be reloaded
for (const auto & m : params.model)
for (const auto & nl : params.n_gpu_layers)
for (const auto & sm : params.split_mode)
for (const auto & mg : params.main_gpu)
for (const auto & ts : params.tensor_split)
for (const auto & nb : params.n_batch)
@ -506,6 +522,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .type_v = */ tv,
/* .n_threads = */ nt,
/* .n_gpu_layers = */ nl,
/* .split_mode = */ sm,
/* .main_gpu = */ mg,
/* .no_kv_offload= */ nkvo,
/* .mul_mat_q = */ mmq,
@ -527,6 +544,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .type_v = */ tv,
/* .n_threads = */ nt,
/* .n_gpu_layers = */ nl,
/* .split_mode = */ sm,
/* .main_gpu = */ mg,
/* .no_kv_offload= */ nkvo,
/* .mul_mat_q = */ mmq,
@ -535,24 +553,6 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
instances.push_back(instance);
}
}
#else
// this ordering separates the prompt and generation tests
for (const auto & n_prompt : params.n_prompt) {
if (n_prompt == 0) {
continue;
}
auto instances_prompt = get_cmd_params_instances_int(params, 0, n_prompt);
instances.insert(instances.end(), instances_prompt.begin(), instances_prompt.end());
}
for (const auto & n_gen : params.n_gen) {
if (n_gen == 0) {
continue;
}
auto instances_gen = get_cmd_params_instances_int(params, n_gen, 0);
instances.insert(instances.end(), instances_gen.begin(), instances_gen.end());
}
#endif
return instances;
}
@ -576,6 +576,7 @@ struct test {
ggml_type type_k;
ggml_type type_v;
int n_gpu_layers;
llama_split_mode split_mode;
int main_gpu;
bool no_kv_offload;
bool mul_mat_q;
@ -597,6 +598,7 @@ struct test {
type_k = inst.type_k;
type_v = inst.type_v;
n_gpu_layers = inst.n_gpu_layers;
split_mode = inst.split_mode;
main_gpu = inst.main_gpu;
no_kv_offload = inst.no_kv_offload;
mul_mat_q = inst.mul_mat_q;
@ -660,7 +662,8 @@ struct test {
"cpu_info", "gpu_info",
"model_filename", "model_type", "model_size", "model_n_params",
"n_batch", "n_threads", "type_k", "type_v",
"n_gpu_layers", "main_gpu", "no_kv_offload",
"n_gpu_layers", "split_mode",
"main_gpu", "no_kv_offload",
"mul_mat_q", "tensor_split",
"n_prompt", "n_gen", "test_time",
"avg_ns", "stddev_ns",
@ -711,7 +714,8 @@ struct test {
cpu_info, gpu_info,
model_filename, model_type, std::to_string(model_size), std::to_string(model_n_params),
std::to_string(n_batch), std::to_string(n_threads), ggml_type_name(type_k), ggml_type_name(type_v),
std::to_string(n_gpu_layers), std::to_string(main_gpu), std::to_string(no_kv_offload),
std::to_string(n_gpu_layers), split_mode_str(split_mode),
std::to_string(main_gpu), std::to_string(no_kv_offload),
std::to_string(mul_mat_q), tensor_split_str,
std::to_string(n_prompt), std::to_string(n_gen), test_time,
std::to_string(avg_ns()), std::to_string(stdev_ns()),
@ -867,6 +871,9 @@ struct markdown_printer : public printer {
if (field == "n_gpu_layers") {
return "ngl";
}
if (field == "split_mode") {
return "sm";
}
if (field == "n_threads") {
return "threads";
}
@ -907,6 +914,9 @@ struct markdown_printer : public printer {
if (params.main_gpu.size() > 1 || params.main_gpu != cmd_params_defaults.main_gpu) {
fields.push_back("main_gpu");
}
if (params.split_mode.size() > 1 || params.split_mode != cmd_params_defaults.split_mode) {
fields.push_back("split_mode");
}
if (params.mul_mat_q.size() > 1 || params.mul_mat_q != cmd_params_defaults.mul_mat_q) {
fields.push_back("mul_mat_q");
}