test_multi_chip_gpu.py

"""
Test for hyperrealistic multi-chip GPU system with full SM and tensor core realism,
using WebSocket-based storage for zero CPU usage.
"""
import time
import numpy as np
from gpu_arch import Chip, OpticalInterconnect

def test_multi_chip_gpu():
    print("\n=== Multi-Chip GPU System with WebSocket Storage Test ===")
    num_chips = 2  # Use 2 for realism, scale up as needed
    num_sms = 4    # Use 4 for realism, scale up as needed

    # Initialize WebSocket storage for all chips
    from websocket_storage import WebSocketGPUStorage
    storage = WebSocketGPUStorage()
    if not storage.wait_for_connection():
        raise RuntimeError("Could not connect to GPU storage server")

    chips = [Chip(
        chip_id=i,
        num_sms=num_sms,
        vram_size_gb=None  # Use unlimited WebSocket storage
    ) for i in range(num_chips)]
    print(f"Created {num_chips} chips with unlimited WebSocket storage, each with {num_sms} SMs.")

    # Connect chips in a ring topology with optical interconnect
    optical_link = OpticalInterconnect(bandwidth_tbps=800, latency_ns=1)
    for i in range(num_chips):
        chips[i].connect_chip(chips[(i+1)%num_chips], optical_link)
        
    # Initialize shared WebSocket storage for cross-chip communication
    for chip in chips:
        chip_state = {
            "chip_id": chip.chip_id,
            "num_sms": num_sms,
            "connected_chips": [(c.chip_id, "optical") for c in chip.connected_chips]
        }
        storage.store_state(f"chips/{chip.chip_id}", "config", chip_state)

    # Run tensor core operations with WebSocket-backed storage
    print("\n=== Testing WebSocket-backed Multi-Chip Operations ===")
    
    # Create test matrices
    matrix_a = [[1.0, 2.0], [3.0, 4.0]]
    matrix_b = [[5.0, 6.0], [7.0, 8.0]]
    
    for chip in chips:
        print(f"\n--- Chip {chip.chip_id} ---")
        
        # Store matrices in WebSocket storage for this chip
        storage.store_tensor(f"chip_{chip.chip_id}/matrix_a", np.array(matrix_a))
        storage.store_tensor(f"chip_{chip.chip_id}/matrix_b", np.array(matrix_b))
        
        # Process using each SM
        for sm_id in range(num_sms):
            sm = chip.get_sm(sm_id)
            
            # Load matrices from WebSocket storage
            matrix_a_data = storage.load_tensor(f"chip_{chip.chip_id}/matrix_a")
            matrix_b_data = storage.load_tensor(f"chip_{chip.chip_id}/matrix_b")
            
            # Perform tensor core operation
            result = sm.tensor_core_matmul(matrix_a_data.tolist(), matrix_b_data.tolist())
            
            # Store result back in WebSocket storage
            storage.store_tensor(f"chip_{chip.chip_id}/sm_{sm_id}/result", np.array(result))
            print(f"SM {sm_id} tensor core matmul result: {result}")
            
        # Test cross-chip communication
        if len(chip.connected_chips) > 0:
            next_chip, link = chip.connected_chips[0]
            
            # Get result from this chip
            result_data = storage.load_tensor(f"chip_{chip.chip_id}/sm_0/result")
            
            # Transfer to next chip through optical link
            transfer_id = f"transfer_chip_{chip.chip_id}_to_{next_chip.chip_id}"
            storage.store_tensor(transfer_id, result_data)
            print(f"Transferred result from Chip {chip.chip_id} to Chip {next_chip.chip_id} via {link.__class__.__name__}")
            for i in range(len(sm.register_file)):
                for j in range(len(sm.register_file[0])):
                    sm.register_file[i][j] = float(i + j)
            for addr in range(sm.shared_mem.size):
                sm.shared_mem.write(addr, float(addr % 10))
            for addr in range(sm.global_mem.size_bytes if sm.global_mem else 0):
                sm.global_mem.write(addr, float(addr % 100))
            # Test tensor core matmul from registers
            reg_result = sm.tensor_core_matmul_from_memory('register', 0, 'register', 0, (2,2), (2,2))
            print(f"SM {sm.sm_id} tensor core matmul from registers: {reg_result}")
            # Test tensor core matmul from shared memory
            shared_result = sm.tensor_core_matmul_from_memory('shared', 0, 'shared', 0, (2,2), (2,2))
            print(f"SM {sm.sm_id} tensor core matmul from shared memory: {shared_result}")
            # Test tensor core matmul from global memory
            global_result = sm.tensor_core_matmul_from_memory('global', 0, 'global', 0, (2,2), (2,2))
            print(f"SM {sm.sm_id} tensor core matmul from global memory: {global_result}")
    print("\n=== Multi-Chip GPU System Test Complete ===")

if __name__ == "__main__":
    start = time.time()
    test_multi_chip_gpu()
    print(f"Test runtime: {time.time()-start:.3f} seconds")