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Ceng23333Ceng23333
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additional remote stash
Signed-off-by: Ceng23333 <[email protected]>
1 parent a3e56c3 commit 26cf06d

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‎build_fixed.sh‎

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#!/bin/bash
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# Fixed build script for InfiniCore
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# This script sets up the environment and builds with proper linker configuration
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echo "Setting up InfiniCore build environment..."
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# Initialize conda
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eval "$(conda shell.bash hook)"
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# Activate the infinicore-env environment
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conda activate infinicore-env
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# Set CUDA_HOME to the conda environment
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export CUDA_HOME=$CONDA_PREFIX
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# Clean up conflicting environment variables
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unset CC
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unset CXX
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unset NVCC_PREPEND_FLAGS
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unset NVCC_APPEND_FLAGS
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unset CUDA_ROOT
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# Use system tools
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export PATH="/usr/bin:$PATH"
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# Create a wrapper for ld that converts -m64 to -m elf_x86_64
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mkdir -p /tmp/ld_wrapper
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cat > /tmp/ld_wrapper/ld << 'EOF'
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#!/bin/bash
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# Convert -m64 to -m elf_x86_64 for system linker compatibility
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args=()
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skip_next=false
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for arg in "$@"; do
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if [ "$skip_next" = true ]; then
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skip_next=false
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continue
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fi
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if [ "$arg" = "-m64" ]; then
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args+=("-m" "elf_x86_64")
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elif [ "$arg" = "-fopenmp" ]; then
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# Skip -fopenmp flag for linker, but add libgomp
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args+=("-lgomp")
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continue
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elif [ "$arg" = "-m" ]; then
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# Skip -m flag and its argument if it's elf_x86_64 (to avoid duplication)
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skip_next=true
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continue
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else
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args+=("$arg")
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fi
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done
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# Add standard C++ library and other required libraries
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args+=("-lstdc++" "-lm" "-lc" "-lgcc_s")
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exec /usr/bin/ld "${args[@]}"
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EOF
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chmod +x /tmp/ld_wrapper/ld
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export PATH="/tmp/ld_wrapper:$PATH"
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echo "Environment setup complete!"
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echo "CUDA_HOME: $CUDA_HOME"
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echo "CONDA_PREFIX: $CONDA_PREFIX"
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# Configure and build
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echo "Configuring xmake..."
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xmake f -c
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echo "Building InfiniCore..."
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xmake build
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echo "Build completed!"

‎example_memory_usage.py‎

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#!/usr/bin/env python3
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"""
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Example script showing how to use InfiniCore memory statistics
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to monitor memory usage during tensor operations.
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"""
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import sys
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import os
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# Add the current directory to Python path
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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try:
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import infinicore
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print("✓ Successfully imported infinicore")
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except ImportError as e:
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print(f"✗ Failed to import infinicore: {e}")
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print("Make sure to build the project first with: xmake build _infinicore")
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sys.exit(1)
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def get_memory_summary():
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"""Get a summary of current memory usage."""
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try:
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device_stats = infinicore.get_device_memory_stats()
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return {
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'allocations': device_stats.allocation[0].current,
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'allocated_bytes': device_stats.allocated_bytes[0].current,
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'active_blocks': device_stats.active[0].current,
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'device_allocations': device_stats.num_device_alloc,
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'device_deallocations': device_stats.num_device_free
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}
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except Exception as e:
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print(f"Warning: Could not get memory stats: {e}")
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return None
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def print_memory_summary(title, stats):
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"""Print a concise memory summary."""
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if stats is None:
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print(f"{title}: Unable to get memory statistics")
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return
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print(f"{title}:")
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print(f" Allocations: {stats['allocations']}")
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print(f" Allocated bytes: {stats['allocated_bytes']:,} bytes ({stats['allocated_bytes'] / 1024 / 1024:.2f} MB)")
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print(f" Active blocks: {stats['active_blocks']}")
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print(f" Device alloc/dealloc: {stats['device_allocations']}/{stats['device_deallocations']}")
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def monitor_memory_usage():
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"""Monitor memory usage during tensor operations."""
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print("=== InfiniCore Memory Usage Monitor ===\n")
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# Initial memory state
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initial_stats = get_memory_summary()
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print_memory_summary("Initial Memory State", initial_stats)
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try:
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# Create some tensors to demonstrate memory usage
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print("\n1. Creating tensors...")
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# Create a large tensor
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print(" Creating 1000x1000 float32 tensor...")
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tensor1 = infinicore.empty((1000, 1000), dtype=infinicore.float32)
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stats_after_tensor1 = get_memory_summary()
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print_memory_summary("After creating tensor1", stats_after_tensor1)
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# Create another tensor
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print("\n Creating 500x500 float32 tensor...")
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tensor2 = infinicore.empty((500, 500), dtype=infinicore.float32)
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stats_after_tensor2 = get_memory_summary()
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print_memory_summary("After creating tensor2", stats_after_tensor2)
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# Create a third tensor
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print("\n Creating 2000x2000 float32 tensor...")
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tensor3 = infinicore.empty((2000, 2000), dtype=infinicore.float32)
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stats_after_tensor3 = get_memory_summary()
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print_memory_summary("After creating tensor3", stats_after_tensor3)
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# Delete some tensors
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print("\n2. Deleting tensors...")
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del tensor1
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stats_after_del1 = get_memory_summary()
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print_memory_summary("After deleting tensor1", stats_after_del1)
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del tensor2
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stats_after_del2 = get_memory_summary()
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print_memory_summary("After deleting tensor2", stats_after_del2)
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# Final cleanup
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print("\n3. Final cleanup...")
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del tensor3
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final_stats = get_memory_summary()
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print_memory_summary("Final Memory State", final_stats)
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# Show memory difference
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if initial_stats and final_stats:
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print(f"\nMemory Usage Summary:")
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print(f" Net allocations: {final_stats['allocations'] - initial_stats['allocations']}")
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print(f" Net allocated bytes: {final_stats['allocated_bytes'] - initial_stats['allocated_bytes']:,} bytes")
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print(f" Net active blocks: {final_stats['active_blocks'] - initial_stats['active_blocks']}")
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print("\n✓ Memory monitoring completed successfully!")
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except Exception as e:
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print(f"✗ Error during memory monitoring: {e}")
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import traceback
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traceback.print_exc()
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def demonstrate_stat_types():
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"""Demonstrate different stat types and their usage."""
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print("\n=== Stat Types Demonstration ===\n")
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try:
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# Get device stats
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device_stats = infinicore.get_device_memory_stats()
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print("StatType.AGGREGATE statistics:")
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print(f" Allocation count: {device_stats.allocation[0].current}")
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print(f" Allocation peak: {device_stats.allocation[0].peak}")
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print(f" Allocation total: {device_stats.allocation[0].allocated}")
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print(f" Allocation freed: {device_stats.allocation[0].freed}")
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print(f"\nStatType.SMALL_POOL statistics:")
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print(f" Allocation count: {device_stats.allocation[1].current}")
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print(f" Allocation peak: {device_stats.allocation[1].peak}")
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print(f"\nStatType.LARGE_POOL statistics:")
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print(f" Allocation count: {device_stats.allocation[2].current}")
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print(f" Allocation peak: {device_stats.allocation[2].peak}")
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print("\n✓ Stat types demonstration completed!")
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except Exception as e:
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print(f"✗ Error during stat types demonstration: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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monitor_memory_usage()
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demonstrate_stat_types()

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