-
-
Save nathanhere/67c4299d30b0e192508cf71fcb9e1cb3 to your computer and use it in GitHub Desktop.
Rough PoC using binary search to find the optimal number of model layers to offload to the GPU, for this LLM and this hardware.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
""" | |
Rough PoC using binary search to find the optimal number of model layers to offload to the GPU, for this LLM and this hardware. | |
""" | |
import time | |
def call_llm(prompt, gpu_layers): | |
# TODO fill in the actual call to LLM here | |
# dummy GPU memory limit | |
test_best_layers = 60 | |
if gpu_layers > test_best_layers: | |
raise("Out of memory!") | |
# dummy sleep | |
time.sleep((test_best_layers + 1 - gpu_layers) * 0.25) | |
return "<response>" | |
max_gpu_layers = 100 | |
def tune_gpu_layers__binary_search(min_gpu_layers, max_gpu_layers, best_gpu_layers, best_time, test_prompt): | |
print(f"tune_gpu_layers: min_gpu_layers={min_gpu_layers}, max_gpu_layers={max_gpu_layers}, best_gpu_layers={best_gpu_layers}, best_time={best_time}, test_prompt={test_prompt}") | |
if (max_gpu_layers - min_gpu_layers) <= 1: | |
return best_gpu_layers | |
current_gpu_layers = round((max_gpu_layers - min_gpu_layers) / 2) + min_gpu_layers | |
print(f"current_gpu_layers = {current_gpu_layers}") | |
start_time = time.time() | |
try: | |
call_llm(test_prompt, current_gpu_layers) | |
except: | |
# out of memory? try less layers | |
print("out of memory? try less layers") | |
max_gpu_layers = current_gpu_layers - 1 | |
return tune_gpu_layers__binary_search(min_gpu_layers, max_gpu_layers, best_gpu_layers, best_time, test_prompt) | |
elapsed = time.time() - start_time | |
if best_time == -1 or elapsed < best_time: | |
best_time = elapsed | |
best_gpu_layers = current_gpu_layers | |
# try more layers, in case we get a better time: | |
print("try more layers") | |
min_gpu_layers = current_gpu_layers | |
return tune_gpu_layers__binary_search(min_gpu_layers, max_gpu_layers, best_gpu_layers, best_time, test_prompt) | |
min_gpu_layers = 1 | |
max_gpu_layers = 100 | |
best_gpu_layers = max_gpu_layers | |
best_time = -1 | |
best_gpu_layers = tune_gpu_layers__binary_search(min_gpu_layers, max_gpu_layers, best_gpu_layers, best_time, "AI is going to") | |
print(f"Best GPU layers for this model, on this hardware: {best_gpu_layers}") |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment