#!/usr/bin/env python3 """ asic_nanokernel_stream_adapter.py - Nanokernel for ASIC Stream Adapter This module designs a nanokernel that exposes ASIC SHA-256 hashing engines as a general-purpose stream adapter. Instead of trying to repurpose ASIC cores for other computations (which is impossible due to burn-in hardware), we accept that ASICs can only do SHA-256 and expose this capability as a stream processor. ARCHITECTURAL PRINCIPLE: The ASIC is a SHA-256 stream processor. The nanokernel makes it accessible as a general-purpose stream adapter. This is similar to the NES unified stack: we don't try to make hardware do something fundamentally different - we repurpose its existing capabilities in a new way. NANOKERNEL RESPONSIBILITIES: 1. UART communication with ASIC chips 2. Stream buffering and chunking 3. Hash result aggregation 4. Error handling and retry logic 5. Clock rate control (via PLL) 6. Power management STREAM ADAPTER INTERFACE: - Input: Arbitrary data stream (bytes) - Output: SHA-256 hash stream (32-byte hashes) - Throughput: Configurable via PLL clock - Latency: Deterministic based on chunk size USE CASES: - Password cracking (SHA-256 password hashes) - Brute force attacks (hash-based verification) - Data integrity verification (real-time hashing) - Merkle tree construction (batch hashing) - Proof-of-work mining (original purpose, but as stream adapter) """ from dataclasses import dataclass from typing import Callable, Optional, List, Tuple from enum import IntEnum import hashlib import time class StreamAdapterMode(IntEnum): """Stream adapter operating modes""" SINGLE_HASH = 0 # Hash single chunk at a time PIPELINE_HASH = 1 # Pipeline multiple chunks BATCH_HASH = 2 # Hash batch of chunks STREAM_HASH = 3 # Continuous stream hashing @dataclass class ASICChip: """ASIC chip configuration""" chip_id: str uart_address: int pll_frequency_mhz: float hash_rate_ghs: float # Giga-hashes per second voltage_v: float # Operating voltage power_w: float # Power consumption in watts temperature_c: float # Temperature in Celsius @dataclass class StreamChunk: """Chunk of data to be hashed""" chunk_id: int data: bytes size_bytes: int timestamp: float @dataclass class HashResult: """Result of hashing a chunk""" chunk_id: int hash_hex: str # SHA-256 hash as hex string hash_bytes: bytes # SHA-256 hash as bytes duration_ms: float chip_id: str @dataclass class StreamAdapterConfig: """Configuration for ASIC stream adapter""" chunk_size_bytes: int = 1024 # 1KB chunks by default pipeline_depth: int = 4 # Number of chunks in pipeline pll_multiplier: float = 1.0 # PLL clock multiplier voltage_target_v: float = 1.0 # Target voltage temperature_max_c: float = 80.0 # Max temperature class NanokernelUART: """ Nanokernel UART communication layer for ASIC chips. Handles low-level UART communication with ASIC chips: - Send TYPE 2 commands (chip commands) - Read/write registers - Control PLL clock frequency - Monitor chip status """ def __init__(self, chip: ASICChip): self.chip = chip self.uart_baud = 115200 # Default baud rate self.uart_config = (8, 0, 1) # 8N1 def send_command(self, command_type: int, address: int, data: bytes) -> bytes: """ Send UART command to ASIC chip. Command structure: 0x55 0xAA TYPE ADDRESS[2] DATA... Response structure: 0xAA 0x55 TYPE DATA... """ # Preamble cmd = bytearray([0x55, 0xAA]) # Command type cmd.append(command_type) # Address (2 bytes, big-endian) cmd.extend(address.to_bytes(2, 'big')) # Data cmd.extend(data) # Simulate UART transmission (in real implementation, this would be actual UART) # For now, return simulated response response = bytearray([0xAA, 0x55]) response.append(command_type) # Response echoes command type response.extend(data) # Response echoes data (simplified) return bytes(response) def read_register(self, register_address: int) -> int: """Read register from ASIC chip""" response = self.send_command(2, register_address, b"\x00\x00") # Simplified: extract register value from response return int.from_bytes(response[4:8], 'big') def write_register(self, register_address: int, value: int) -> bool: """Write register to ASIC chip""" data = value.to_bytes(4, 'big') response = self.send_command(2, register_address, data) # Simplified: check if write succeeded return len(response) > 4 def set_pll_frequency(self, frequency_mhz: float) -> bool: """Set PLL clock frequency""" # PLL register is at address 0x08 # Formula: fPLL0 = fCLKI x FBDIV / (REFDIV x POSTDIV1 x POSTDIV2) # Simplified: write frequency value to PLL register pll_value = int(frequency_mhz * 1e6) return self.write_register(0x08, pll_value) def get_chip_status(self) -> dict: """Get chip status (temperature, hash rate, etc.)""" # Simplified: read status registers return { "temperature": self.chip.temperature_c, "hash_rate": self.chip.hash_rate_ghs, "voltage": self.chip.voltage_v, "power": self.chip.power_w } class StreamAdapterNanokernel: """ Nanokernel for ASIC stream adapter. Responsibilities: 1. UART communication with ASIC chips 2. Stream buffering and chunking 3. Hash result aggregation 4. Error handling and retry logic 5. Clock rate control (via PLL) 6. Power management The nanokernel exposes the ASIC as a general-purpose stream processor. Input: arbitrary data stream → Output: SHA-256 hash stream """ def __init__(self, chips: List[ASICChip], config: StreamAdapterConfig): self.chips = chips self.config = config self.uart_layers = [NanokernelUART(chip) for chip in chips] self.mode = StreamAdapterMode.STREAM_HASH self.pipeline: List[StreamChunk] = [] self.results: List[HashResult] = [] self.total_chunks_hashed = 0 self.total_bytes_hashed = 0 self.start_time = time.time() def initialize(self) -> bool: """Initialize nanokernel and ASIC chips""" print("Nanokernel initialization...") # Initialize UART layers for uart in self.uart_layers: print(f" Initializing UART for chip {uart.chip.chip_id}") # Set PLL frequency for all chips target_pll = self.chips[0].pll_frequency_mhz * self.config.pll_multiplier for uart in self.uart_layers: success = uart.set_pll_frequency(target_pll) print(f" Set PLL to {target_pll:.2f} MHz: {success}") print("Nanokernel initialization complete") return True def chunk_stream(self, data: bytes) -> List[StreamChunk]: """Split data stream into chunks""" chunks = [] chunk_size = self.config.chunk_size_bytes num_chunks = (len(data) + chunk_size - 1) // chunk_size for i in range(num_chunks): start = i * chunk_size end = min(start + chunk_size, len(data)) chunk_data = data[start:end] chunk = StreamChunk( chunk_id=i, data=chunk_data, size_bytes=len(chunk_data), timestamp=time.time() ) chunks.append(chunk) return chunks def hash_chunk(self, chunk: StreamChunk, chip_index: int = 0) -> HashResult: """ Hash a single chunk using ASIC chip. In real implementation, this would: 1. Send chunk data to ASIC via UART 2. Wait for hash result 3. Return hash result For simulation, we use Python's hashlib. """ start_time = time.time() # Simulate ASIC hashing (in real implementation, send to ASIC) # Use Python's hashlib for simulation hash_obj = hashlib.sha256(chunk.data) hash_bytes = hash_obj.digest() hash_hex = hash_obj.hexdigest() duration_ms = (time.time() - start_time) * 1000 return HashResult( chunk_id=chunk.chunk_id, hash_hex=hash_hex, hash_bytes=hash_bytes, duration_ms=duration_ms, chip_id=self.chips[chip_index].chip_id ) def hash_stream(self, data: bytes) -> List[HashResult]: """ Hash entire data stream using stream adapter. Process: 1. Chunk the stream 2. Hash each chunk (pipeline if configured) 3. Aggregate results 4. Return hash stream """ chunks = self.chunk_stream(data) results = [] print(f"Hashing {len(data)} bytes in {len(chunks)} chunks...") for chunk in chunks: # Round-robin chip selection for load balancing chip_index = chunk.chunk_id % len(self.chips) result = self.hash_chunk(chunk, chip_index) results.append(result) self.total_chunks_hashed += 1 self.total_bytes_hashed += chunk.size_bytes self.results.extend(results) return results def hash_stream_pipeline(self, data: bytes) -> List[HashResult]: """ Hash stream with pipeline parallelization. Pipeline depth determines how many chunks are processed in parallel. """ chunks = self.chunk_stream(data) results = [] print(f"Pipeline hashing {len(data)} bytes in {len(chunks)} chunks (depth={self.config.pipeline_depth})...") # Simplified pipeline: process chunks in batches batch_size = self.config.pipeline_depth for i in range(0, len(chunks), batch_size): batch = chunks[i:i + batch_size] batch_results = [] for chunk in batch: chip_index = chunk.chunk_id % len(self.chips) result = self.hash_chunk(chunk, chip_index) batch_results.append(result) self.total_chunks_hashed += 1 self.total_bytes_hashed += chunk.size_bytes results.extend(batch_results) self.results.extend(results) return results def get_statistics(self) -> dict: """Get stream adapter statistics""" elapsed_time = time.time() - self.start_time throughput_mbps = (self.total_bytes_hashed / 1e6) / elapsed_time if elapsed_time > 0 else 0 return { "total_chunks_hashed": self.total_chunks_hashed, "total_bytes_hashed": self.total_bytes_hashed, "elapsed_time_seconds": elapsed_time, "throughput_mbps": throughput_mbps, "chunks_per_second": self.total_chunks_hashed / elapsed_time if elapsed_time > 0 else 0, "num_chips": len(self.chips), "mode": self.mode.name } def shutdown(self): """Shutdown nanokernel and ASIC chips""" print("Nanokernel shutdown...") # Reset PLL to default frequency for uart in self.uart_layers: uart.set_pll_frequency(self.chips[0].pll_frequency_mhz) print("Nanokernel shutdown complete") # ============================================================================ # DEMONSTRATION # ============================================================================ def demonstrate_asic_stream_adapter(): """Demonstrate ASIC stream adapter nanokernel""" print("=" * 80) print("ASIC STREAM ADAPTER NANOKERNEL DEMONSTRATION") print("=" * 80) print() # Configure ASIC chips (simulated BM1397 chips) chips = [ ASICChip( chip_id="asic_001", uart_address=0x00, pll_frequency_mhz=2400.0, hash_rate_ghs=50.0, voltage_v=1.0, power_w=3000.0, temperature_c=45.0 ), ASICChip( chip_id="asic_002", uart_address=0x04, pll_frequency_mhz=2400.0, hash_rate_ghs=50.0, voltage_v=1.0, power_w=3000.0, temperature_c=47.0 ), ASICChip( chip_id="asic_003", uart_address=0x08, pll_frequency_mhz=2400.0, hash_rate_ghs=50.0, voltage_v=1.0, power_w=3000.0, temperature_c=46.0 ) ] # Configure stream adapter config = StreamAdapterConfig( chunk_size_bytes=1024, pipeline_depth=4, pll_multiplier=1.0, voltage_target_v=1.0, temperature_max_c=80.0 ) # Initialize nanokernel nanokernel = StreamAdapterNanokernel(chips, config) nanokernel.initialize() print() # Test data stream test_data = b"This is a test data stream for the ASIC stream adapter nanokernel. " * 100 print(f"Test data size: {len(test_data)} bytes") print() # Hash stream (single-threaded) print("MODE: SINGLE_HASH") print("-" * 80) nanokernel.mode = StreamAdapterMode.SINGLE_HASH results_single = nanokernel.hash_stream(test_data) print(f"Hashed {len(results_single)} chunks") for result in results_single[:3]: print(f" Chunk {result.chunk_id}: {result.hash_hex[:16]}... ({result.duration_ms:.2f}ms)") if len(results_single) > 3: print(f" ... and {len(results_single) - 3} more") print() # Hash stream (pipeline) print("MODE: PIPELINE_HASH") print("-" * 80) nanokernel.mode = StreamAdapterMode.PIPELINE_HASH results_pipeline = nanokernel.hash_stream_pipeline(test_data) print(f"Hashed {len(results_pipeline)} chunks") for result in results_pipeline[:3]: print(f" Chunk {result.chunk_id}: {result.hash_hex[:16]}... ({result.duration_ms:.2f}ms)") if len(results_pipeline) > 3: print(f" ... and {len(results_pipeline) - 3} more") print() # Statistics print("STATISTICS") print("-" * 80) stats = nanokernel.get_statistics() for key, value in stats.items(): print(f" {key}: {value}") print() # Shutdown nanokernel.shutdown() print() # Comparison with NES unified stack print("=" * 80) print("COMPARISON WITH NES UNIFIED STACK") print("=" * 80) print(""" NES Unified Stack: - 1985 hardware → 2026 neural compression/upload tech substrate - Controller ports → bidirectional UART - Audio lines → DSP math computation - Voltage levels → computational substrate - 256×240 → 640×480 via microgrid emulation - Key insight: Single-purpose hardware can be repurposed with creative architecture ASIC Stream Adapter: - SHA-256 ASIC → general-purpose stream adapter - UART interface → stream communication - SHA-256 cores → hash stream processor - PLL control → throughput control - Voltage control → power management - Key insight: Accept hardware limitations, expose capability as stream adapter Difference: - NES: Repurposed existing interfaces for new computational purposes - ASIC: Existed existing capability (SHA-256) as general stream adapter Similarity: - Both use nanokernel to bridge hardware to new use cases - Both accept hardware limitations and work within them - Both prove that "single-purpose" is a design choice, not physical limitation """) # Use cases print("=" * 80) print("STREAM ADAPTER USE CASES") print("=" * 80) print(""" 1. Password Cracking: - Stream of candidate passwords → SHA-256 hash stream - Compare against target hash - Real-time verification 2. Brute Force Attacks: - Stream of candidate values → SHA-256 hash stream - Parallel verification across multiple chips - High-throughput exploration 3. Data Integrity Verification: - Stream of data blocks → SHA-256 hash stream - Compare against known good hashes - Real-time corruption detection 4. Merkle Tree Construction: - Stream of data blocks → SHA-256 hash stream - Build Merkle tree from hash stream - Batch verification 5. Proof-of-Work Mining (Original Purpose): - Stream of nonces → SHA-256 hash stream - Find hash below target difficulty - But now as general stream adapter, not hardcoded to Bitcoin Key Insight: The ASIC stream adapter doesn't try to make the ASIC do something other than SHA-256. It accepts that the ASIC can only do SHA-256 and exposes this as a general-purpose stream processor. This is the same principle as the NES unified stack: work within hardware limitations, don't fight them. """) if __name__ == "__main__": demonstrate_asic_stream_adapter()