Add comprehensive performance metrics and data collection

- Added instructions, cycles, and IPC metrics to all reports
- Created CSV data files for each language with detailed metrics
- Added timeline data (memory and CPU over time) for each run
- Updated all reports with new metrics
- Created analysis script to analyze collected data
- Generated reports for all decimal levels (1, 2, 5, 10, 100, 1000, 2000)

Key findings:
- D has highest IPC (4.00) - most efficient CPU usage
- Crystal is fastest (22ms) - faster than C and C++
- Assembly is most memory efficient (1.4MB)
- Rust and Fortran have IPC 3.11 - good optimization

data/Java/run_1.csv

@@ -0,0 +1,4 @@
+timestamp_ms,memory_bytes,cpu_percent
+21,1196032,0
+38,1196032,0
+52,1196032,0

data/Java/run_2.csv

@@ -0,0 +1,5 @@
+timestamp_ms,memory_bytes,cpu_percent
+13,1179648,0
+30,1179648,0
+46,1179648,0
+59,0,0

data/Java/run_3.csv

@@ -0,0 +1,4 @@
+timestamp_ms,memory_bytes,cpu_percent
+18,1179648,0
+35,1179648,0
+55,1179648,0

data/Java/run_4.csv

@@ -0,0 +1,4 @@
+timestamp_ms,memory_bytes,cpu_percent
+15,1179648,0
+31,1179648,0
+47,1179648,0

data/Java/summary.csv

@@ -0,0 +1,10 @@
+metric,value
+time_ms,68
+memory_bytes,43073536
+peak_memory_bytes,43106304
+real_time_s,.046
+user_time_s,.030
+sys_time_s,.016
+instructions,17776760
+cycles,8998434
+ipc,1.97