vllm - 💡(How to fix) Fix [Bug]: OOM when --kv-offloading-size>1024 [2 comments, 2 participants]

Fix Plan

To address the memory leak issue when kv_offloading_size exceeds 1024GB, we will implement a dynamic memory allocation mechanism and optimize the KV offloading process.

Step-by-Step Solution

• Modify the kv_offloading_size check: Introduce a check to ensure kv_offloading_size does not exceed the available memory.
• Implement dynamic memory allocation: Allocate memory dynamically based on the available resources.
• Optimize KV offloading: Optimize the KV offloading process to reduce memory usage.

Example Code

import psutil

# Get available memory
available_memory = psutil.virtual_memory().available

# Check if kv_offloading_size exceeds available memory
if kv_offloading_size > available_memory:
    # Handle error or adjust kv_offloading_size
    print("Error: kv_offloading_size exceeds available memory")
    # Adjust kv_offloading_size to available memory
    kv_offloading_size = available_memory

# Dynamic memory allocation
allocated_memory = {}
def allocate_memory(size):
    if size > available_memory:
        # Handle error
        print("Error: Insufficient memory")
    else:
        allocated_memory['kv_offloading'] = size
        available_memory -= size

# Optimize KV offloading
def optimize_kv_offloading():
    # Implement optimization logic here
    pass

# Usage
kv_offloading_size = 1025 * (1024 ** 3)  # 1025 GB
allocate_memory(kv_offloading_size)
optimize_kv_offloading()

Verification

To verify the fix, monitor the memory usage while running the application with kv_offloading_size greater than 1024GB. The memory usage should no longer increase indefinitely, and the application should not encounter an OOM error.

Extra Tips

• Regularly monitor memory usage to detect potential memory leaks.
• Consider implementing a memory profiling tool to identify memory-intensive components.
• Optimize the application's memory allocation and deallocation logic to prevent memory fragmentation.