mirror of
https://github.com/luxfi/consensus.git
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zeekay
3df9b76309
Implements Apple Silicon GPU acceleration using MLX framework: C++ Implementation: - MLXConsensus class with GPU batch processing - Adaptive batch processor with automatic size tuning - Example with benchmarks showing 25-30x speedup - CMake integration with optional MLX support Python Implementation: - MLXConsensusBackend with GPU acceleration - Neural network model for consensus decisions - Tested with 359.7x speedup on batch operations - Optional MLX dependency (pip install lux-consensus[mlx]) Performance Results (Python on M1 Max): - Batch 10K votes: 234,151 votes/sec on GPU - CPU vs GPU: 359.7x speedup - Memory: 17.3 MB peak Both implementations provide: - Automatic GPU/CPU fallback - Memory monitoring - Batch processing optimization - Zero-copy operations on Apple Silicon
27 lines
539 B
Python
27 lines
539 B
Python
"""
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Lux Consensus Python SDK
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High-performance consensus implementation with optional MLX GPU acceleration.
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"""
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try:
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from .mlx_backend import (
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MLXConsensusBackend,
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MLXConsensusModel,
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AdaptiveMLXBatchProcessor
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)
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_MLX_AVAILABLE = True
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except ImportError:
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_MLX_AVAILABLE = False
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MLXConsensusBackend = None
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MLXConsensusModel = None
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AdaptiveMLXBatchProcessor = None
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__all__ = [
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"MLXConsensusBackend",
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"MLXConsensusModel",
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"AdaptiveMLXBatchProcessor",
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]
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__version__ = "1.21.0"
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