[midend/lib/Conversion]TOSA:ReduceSumOP Vectorize Optimization

examples/BuddyDeepSeekR1/AnalyseDialectOps.py

@@ -0,0 +1,87 @@
+#!/usr/bin/env python3
+
+import os
+import re
+from collections import Counter, defaultdict
+from pathlib import Path
+
+def extract_dialect_ops(mlir_file_path):
+    """
+    Extract operations from all dialects in an MLIR file and count their occurrences.
+
+    Args:
+        mlir_file_path (str): Path to the MLIR file
+
+    Returns:
+        dict: Dictionary containing dialect names as keys and Counter objects as values
+    """
+    # Read the MLIR file
+    with open(mlir_file_path, 'r') as f:
+        content = f.read()
+
+    # Find all operations using regex
+    # This pattern matches lines that contain operation names with dialect prefix
+    # Excludes numbers and common non-dialect prefixes
+    op_pattern = r'([a-zA-Z_][a-zA-Z0-9_]*)\.([a-zA-Z_][a-zA-Z0-9_]*)'
+    all_ops = re.findall(op_pattern, content)
+
+    # Group operations by dialect
+    dialect_ops = defaultdict(Counter)
+    for dialect, op in all_ops:
+        # Skip common non-dialect prefixes
+        if dialect.lower() in ['func', 'module', 'memref', 'arith', 'builtin']:
+            continue
+        dialect_ops[dialect][op] += 1
+
+    return dialect_ops
+
+def main():
+    # Get the directory of the current script
+    current_dir = Path(__file__).parent
+
+    # Construct path to subgraph0.mlir
+    mlir_file = current_dir / 'subgraph0.mlir'
+
+    if not mlir_file.exists():
+        print(f"Error: {mlir_file} not found")
+        return
+
+    # Extract and count operations by dialect
+    dialect_ops = extract_dialect_ops(str(mlir_file))
+
+    # Print results
+    print("\nMLIR Operation Statistics:")
+    print("=" * 60)
+    print(f"{'Dialect':<20} {'Operation':<30} {'Count':<10}")
+    print("=" * 60)
+
+    total_ops = 0
+    total_unique_ops = 0
+
+    # Sort dialects by total operation count
+    sorted_dialects = sorted(
+        dialect_ops.items(),
+        key=lambda x: sum(x[1].values()),
+        reverse=True
+    )
+
+    for dialect, ops in sorted_dialects:
+        dialect_total = sum(ops.values())
+        total_ops += dialect_total
+        total_unique_ops += len(ops)
+
+        print(f"\n{dialect} (Total: {dialect_total} ops)")
+        print("-" * 60)
+
+        # Sort operations by count
+        sorted_ops = sorted(ops.items(), key=lambda x: x[1], reverse=True)
+        for op, count in sorted_ops:
+            print(f"{'':<20} {op:<30} {count:<10}")
+
+    print("\n" + "=" * 60)
+    print(f"Total dialects: {len(dialect_ops)}")
+    print(f"Total unique operations: {total_unique_ops}")
+    print(f"Total operation instances: {total_ops}")
+
+if __name__ == "__main__":
+    main()

examples/BuddyDeepSeekR1/makefile

@@ -0,0 +1,22 @@
+#!/bin/bash
+BUDDY_OPT := ../../build/bin/buddy-opt
+MLIR_OPT := ../../llvm/build/bin/mlir-opt
+MLIR_TRANSLATE := ../../llvm/build/bin/mlir-translate
+MLIR_CPU_RUNNER := ../../llvm/build/bin/mlir-cpu-runner
+LLC := ../../llvm/build/bin/llc
+OPT_FLAG := -O0
+
+ifeq ($(shell uname),Linux)
+MLIR_RUNNER_UTILS := ../../llvm/build/lib/libmlir_runner_utils.so
+MLIR_C_RUNNER_UTILS := ../../llvm/build/lib/libmlir_c_runner_utils.so
+LIB_OMP := ../../llvm/build/lib/libomp.so
+MTRIPLE := x86_64-unknown-linux-gnu
+else ifeq ($(shell uname),Darwin)
+MLIR_RUNNER_UTILS := ../../llvm/build/lib/libmlir_runner_utils.dylib
+MLIR_C_RUNNER_UTILS := ../../llvm/build/lib/libmlir_c_runner_utils.dylib
+MTRIPLE := x86_64-apple-darwin
+endif
+
+lower-deepseek-r1-tosa:
+	@${MLIR_OPT} ./subgraph0.mlir \
+		-pass-pipeline "builtin.module(func.func(tosa-to-linalg-named),func.func(tosa-to-linalg),func.func(tosa-to-tensor),func.func(tosa-to-arith))" -o ./subgraph0-lower.mlir

examples/BuddyNext/compare_outputs.sh

@@ -0,0 +1,121 @@
+#!/bin/bash
+
+# 设置颜色输出
+GREEN='\033[0;32m'
+RED='\033[0;31m'
+NC='\033[0m' # No Color
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+
+# 检查命令行参数
+if [ $# -ne 2 ]; then
+    echo -e "${YELLOW}Usage: $0 <command1> <command2>${NC}"
+    echo "Example: $0 'next-reduce-sum-run' 'next-reduce-sum-vec-manual-run'"
+    exit 1
+fi
+
+CMD1="$1"
+CMD2="$2"
+RUNS=10
+
+# 创建临时文件存储输出
+OUTPUT1=$(mktemp)
+OUTPUT2=$(mktemp)
+PROCESSED1=$(mktemp)
+SPEEDUPS=$(mktemp)
+
+# 提取时间数据
+extract_time() {
+    local file="$1"
+    grep -o '[0-9]\+\.[0-9]\+e[-+]\?[0-9]\+\|[0-9]\+\.[0-9]\+' "$file"
+}
+
+# 转换时间为秒
+convert_to_seconds() {
+    local time_val="$1"
+    if [[ $time_val =~ e ]]; then
+        echo "$time_val" | sed 's/e/*10^/' | bc -l
+    else
+        printf "%.9f" $time_val
+    fi
+}
+
+# 计算平均值
+calculate_mean() {
+    local file="$1"
+    local sum=0
+    local count=0
+    while read -r line; do
+        sum=$(echo "$sum + $line" | bc -l)
+        count=$((count + 1))
+    done < "$file"
+    if [ $count -gt 0 ]; then
+        echo "scale=9; $sum / $count" | bc -l
+    else
+        echo "0"
+    fi
+}
+
+echo -e "${BLUE}Running each version $RUNS times...${NC}"
+
+# 运行两个命令并计算每次的加速比
+for ((i=1; i<=$RUNS; i++)); do
+    echo -ne "\rRun $i/$RUNS"
+
+    # 运行第一个命令
+    TEMP_OUT1=$(mktemp)
+    make $CMD1 > "$TEMP_OUT1" 2>/dev/null
+    TIME1=$(extract_time "$TEMP_OUT1")
+    if [ -n "$TIME1" ]; then
+        TIME1=$(convert_to_seconds "$TIME1")
+    fi
+
+    # 运行第二个命令
+    TEMP_OUT2=$(mktemp)
+    make $CMD2 > "$TEMP_OUT2" 2>/dev/null
+    TIME2=$(extract_time "$TEMP_OUT2")
+    if [ -n "$TIME2" ]; then
+        TIME2=$(convert_to_seconds "$TIME2")
+    fi
+
+    # 保存第一次运行的输出用于比较
+    if [ $i -eq 1 ]; then
+        grep "data =" "$TEMP_OUT1" | sed 's/base@ = [^[:space:]]*/base@ = <addr>/g' > "$PROCESSED1"
+        grep "data =" "$TEMP_OUT2" | sed 's/base@ = [^[:space:]]*/base@ = <addr>/g' > "$OUTPUT2"
+    fi
+
+    # 计算这次运行的加速比
+    if [ -n "$TIME1" ] && [ -n "$TIME2" ] && [ "$TIME1" != "0" ] && [ "$TIME2" != "0" ]; then
+        echo "scale=9; $TIME1/$TIME2" | bc -l >> "$SPEEDUPS"
+    fi
+
+    rm "$TEMP_OUT1" "$TEMP_OUT2"
+done
+echo
+
+# 比较数据输出
+echo -e "\n${BLUE}Comparing output data:${NC}"
+if diff "$PROCESSED1" "$OUTPUT2" > /dev/null; then
+    echo -e "${GREEN}✓ Outputs match! Both versions produce the same results.${NC}"
+else
+    echo -e "${RED}✗ Outputs differ! Found differences:${NC}"
+    echo "----------------------------------------"
+    diff "$PROCESSED1" "$OUTPUT2"
+    echo "----------------------------------------"
+fi
+
+# 计算加速比的均值
+echo -e "\n${BLUE}Performance Comparison:${NC}"
+SPEEDUP_MEAN=$(calculate_mean "$SPEEDUPS")
+
+if [ -n "$SPEEDUP_MEAN" ] && [ "$SPEEDUP_MEAN" != "0" ]; then
+    if [ $(echo "$SPEEDUP_MEAN > 1" | bc -l) -eq 1 ]; then
+        printf "${GREEN}Second version is %.2fx faster${NC}\n" "$SPEEDUP_MEAN"
+    else
+        SLOWDOWN=$(echo "scale=2; 1/$SPEEDUP_MEAN" | bc -l)
+        printf "${RED}Second version is %.2fx slower${NC}\n" "$SLOWDOWN"
+    fi
+fi
+
+# 清理临时文件
+rm "$OUTPUT1" "$OUTPUT2" "$PROCESSED1" "$SPEEDUPS"