15 files changed, 3300 insertions, 0 deletions
diff --git a/decompress/analyze_bw.py b/decompress/analyze_bw.py
new file mode 100755
index 0000000..e4fab84
--- /dev/null
+++ b/decompress/analyze_bw.py
@@ -0,0 +1,345 @@
+#!/usr/bin/env python3
+
+import argparse
+import csv
+import sys
+from collections import defaultdict
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+KIBPS_TO_UNIT = {
+    "KiBps": 1.0,
+    "MiBps": 1.0 / 1024.0,
+    "GiBps": 1.0 / (1024.0 * 1024.0),
+}
+
+
+UNIT_DISPLAY = {
+    "KiBps": "KiB/s",
+    "MiBps": "MiB/s",
+    "GiBps": "GiB/s",
+}
+
+
+def format_bytes(n) -> str:
+    """
+    Format size using the largest readable unit.
+
+    Examples:
+      246132K   -> 246M
+      2097148K  -> 2.0G
+
+    Notes:
+      - CSV normally gives integer bytes.
+      - This also accepts strings like "246132K" if needed.
+      - M is shown as rounded whole MB.
+      - G/T are shown with one decimal place.
+    """
+    if isinstance(n, str):
+        s = n.strip()
+        suffix = s[-1].upper()
+
+        if suffix in {"K", "M", "G", "T"}:
+            value = float(s[:-1])
+            # Interpret suffix input as decimal-style units.
+            scale = {
+                "K": 1_000,
+                "M": 1_000_000,
+                "G": 1_000_000_000,
+                "T": 1_000_000_000_000,
+            }[suffix]
+            n = int(value * scale)
+        else:
+            n = int(s)
+
+    n = int(n)
+
+    # Use G/T when the value is large enough.
+    if n >= 1024 ** 4:
+        return f"{n / (1024 ** 4):.2f}T"
+
+    if n >= 1024 ** 3:
+        return f"{n / (1024 ** 3):.2f}G"
+
+    if n >= 1_000_000:
+        return f"{round(n / 1_000_000)}M"
+
+    if n >= 1_000:
+        return f"{round(n / 1_000)}K"
+
+    return f"{n}B"
+
+def experiment_label(path: str) -> str:
+    name = Path(path).name
+
+    if name.startswith("bw_") and name.endswith(".csv"):
+        return name[len("bw_") : -len(".csv")]
+
+    if name.startswith("bandwidth_") and name.endswith(".csv"):
+        return name[len("bandwidth_") : -len(".csv")]
+
+    return Path(path).stem
+
+
+def percentile(values, p: float) -> float:
+    return float(np.percentile(np.array(values, dtype=float), p))
+
+
+def read_bw_csv(path: str, unit: str):
+    grouped = defaultdict(list)
+
+    with open(path, newline="") as f:
+        reader = csv.DictReader(f)
+
+        if reader.fieldnames is None:
+            raise ValueError(f"{path}: empty CSV or missing header")
+
+        fieldnames = [name.strip() for name in reader.fieldnames]
+        if fieldnames != ["bytes", "bw_KiBps"]:
+            raise ValueError(
+                f"{path}: expected header 'bytes,bw_KiBps', got: {','.join(fieldnames)}"
+            )
+
+        for line_no, row in enumerate(reader, start=2):
+            try:
+                nbytes = int(row["bytes"].strip())
+                bw_kibps = float(row["bw_KiBps"].strip())
+            except Exception as e:
+                raise ValueError(f"{path}: invalid row at line {line_no}: {row} ({e})")
+
+            grouped[nbytes].append(bw_kibps * KIBPS_TO_UNIT[unit])
+
+    return grouped
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description="Create grouped bandwidth bar graph from bw_*.csv files."
+    )
+    parser.add_argument(
+        "inputs",
+        nargs="+",
+        help="Input CSV files with header: bytes,bw_KiBps. Recommended naming: bw_<label>.csv",
+    )
+    parser.add_argument(
+        "--unit",
+        default="GiBps",
+        choices=sorted(KIBPS_TO_UNIT.keys()),
+        help="Output bandwidth unit. Input is always bw_KiBps. Default: GiBps",
+    )
+    parser.add_argument(
+        "--out",
+        default="bandwidth_bar.png",
+        help="Output bar graph filename. Default: bandwidth_bar.png",
+    )
+    parser.add_argument(
+        "--no-errorbar",
+        action="store_true",
+        help="Disable standard-deviation error bars.",
+    )
+    parser.add_argument(
+        "--legend-outside",
+        action="store_true",
+        help="Place legend outside the plot.",
+    )
+
+    args = parser.parse_args()
+
+    output_unit = UNIT_DISPLAY[args.unit]
+    all_data = []
+
+    for path in args.inputs:
+        try:
+            grouped = read_bw_csv(path, args.unit)
+        except ValueError as e:
+            print(f"ERROR: {e}", file=sys.stderr)
+            return 1
+
+        if not grouped:
+            print(f"ERROR: {path}: no data rows", file=sys.stderr)
+            return 1
+
+        all_data.append(
+            {
+                "path": path,
+                "label": experiment_label(path),
+                "grouped": grouped,
+            }
+        )
+
+    print("Bandwidth summary")
+    print("=================")
+    print(f"input_files: {len(all_data)}")
+    print(f"input_unit:  KiB/s")
+    print(f"output_unit: {output_unit}")
+    print()
+
+    print(
+        f"{'file_label':>18} {'bytes':>14} {'size':>8} {'n':>8} "
+        f"{'min':>12} {'avg':>12} {'std':>12} "
+        f"{'p1':>12} {'p5':>12} {'p10':>12} {'p50':>12} "
+        f"{'p90':>12} {'p99':>12} {'max':>12}"
+    )
+
+    # stats[label][nbytes] = dict(...)
+    stats = defaultdict(dict)
+    all_sizes = set()
+
+    for item in all_data:
+        file_label = item["label"]
+        grouped = item["grouped"]
+
+        for nbytes in sorted(grouped.keys()):
+            bws = np.array(grouped[nbytes], dtype=float)
+            all_sizes.add(nbytes)
+
+            min_v = float(np.min(bws))
+            avg = float(np.mean(bws))
+            std = float(np.std(bws))
+            p1 = percentile(bws, 1)
+            p5 = percentile(bws, 5)
+            p10 = percentile(bws, 10)
+            p50 = percentile(bws, 50)
+            p90 = percentile(bws, 90)
+            p99 = percentile(bws, 99)
+            max_v = float(np.max(bws))
+
+            size_label = format_bytes(nbytes)
+
+            print(
+                f"{file_label:>18} {nbytes:14d} {size_label:>8} {len(bws):8d} "
+                f"{min_v:12.6f} {avg:12.6f} {std:12.6f} "
+                f"{p1:12.6f} {p5:12.6f} {p10:12.6f} {p50:12.6f} "
+                f"{p90:12.6f} {p99:12.6f} {max_v:12.6f}"
+            )
+
+            stats[file_label][nbytes] = {
+                "n": len(bws),
+                "avg": avg,
+                "std": std,
+                "min": min_v,
+                "max": max_v,
+                "p50": p50,
+                "p90": p90,
+                "p99": p99,
+            }
+
+    sizes = sorted(all_sizes)
+    size_labels = [format_bytes(s) for s in sizes]
+    experiment_labels = [item["label"] for item in all_data]
+
+    x = np.arange(len(sizes))
+    num_experiments = len(experiment_labels)
+
+    # Bar width shrinks as the number of experiments grows.
+    total_group_width = 0.82
+    bar_width = total_group_width / max(1, num_experiments)
+
+    fig_width = max(9, len(sizes) * 1.4)
+    fig, ax = plt.subplots(figsize=(fig_width, 6))
+
+    for idx, label in enumerate(experiment_labels):
+        offsets = x - total_group_width / 2 + bar_width / 2 + idx * bar_width
+
+        means = []
+        errors = []
+
+        for nbytes in sizes:
+            if nbytes in stats[label]:
+                means.append(stats[label][nbytes]["avg"])
+                errors.append(stats[label][nbytes]["std"])
+            else:
+                means.append(np.nan)
+                errors.append(0.0)
+
+        if args.no_errorbar:
+            ax.bar(
+                offsets,
+                means,
+                width=bar_width,
+                label=label,
+            )
+        else:
+            ax.bar(
+                offsets,
+                means,
+                width=bar_width,
+                yerr=errors,
+                capsize=3,
+                label=label,
+            )
+
+    # Automatically cut off the bottom of the y-axis to make bar differences visible.
+    # This intentionally truncates the y-axis.
+    all_bar_values = []
+    all_error_values = []
+
+    for label in experiment_labels:
+        for nbytes in sizes:
+            if nbytes in stats[label]:
+                all_bar_values.append(stats[label][nbytes]["avg"])
+                all_error_values.append(stats[label][nbytes]["std"])
+
+    if all_bar_values:
+        values = np.array(all_bar_values, dtype=float)
+        errors = np.array(all_error_values, dtype=float)
+
+        if args.no_errorbar:
+            low = float(np.nanmin(values))
+            high = float(np.nanmax(values))
+        else:
+            low = float(np.nanmin(values - errors))
+            high = float(np.nanmax(values + errors))
+
+        span = max(high - low, 1e-9)
+
+        # Leave 10% padding below the lowest visible bar/error.
+        auto_bottom = low - 0.10 * span
+
+        # Avoid negative y-axis for bandwidth.
+        auto_bottom = max(0.0, auto_bottom)
+
+        ax.set_ylim(bottom=auto_bottom)
+
+        ax.text(
+            0.01,
+            0.98,
+            "Y-axis truncated",
+            transform=ax.transAxes,
+            va="top",
+            fontsize=9,
+        )
+
+    ax.set_xlabel("Transfer size")
+    ax.set_ylabel(f"Bandwidth ({output_unit})")
+    ax.set_title("DMA Bandwidth by Transfer Size")
+    ax.set_xticks(x)
+    ax.set_xticklabels(size_labels)
+    ax.grid(axis="y", linestyle="--", alpha=0.6)
+
+    if args.legend_outside:
+        ax.legend(
+            title="Experiment",
+            fontsize=8,
+            loc="center left",
+            bbox_to_anchor=(1.02, 0.5),
+        )
+        fig.tight_layout(rect=[0, 0, 0.80, 1])
+    else:
+        ax.legend(title="Experiment", fontsize=8)
+        fig.tight_layout()
+
+    fig.savefig(args.out, dpi=200)
+    plt.close(fig)
+
+    print()
+    print(f"Wrote bar graph: {args.out}")
+
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/decompress/analyze_time.py b/decompress/analyze_time.py
new file mode 100755
index 0000000..8f467e4
--- /dev/null
+++ b/decompress/analyze_time.py
@@ -0,0 +1,332 @@
+#!/usr/bin/env python3
+
+import argparse
+import csv
+import sys
+from collections import defaultdict
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+USEC_TO_UNIT = {
+    "sec": 1.0 / 1_000_000.0,
+    "msec": 1.0 / 1_000.0,
+    "usec": 1.0,
+    "nsec": 1_000.0,
+}
+
+
+LINESTYLES = ["-", "--", "-.", ":"]
+MARKERS = ["o", "s", "^", "D", "v", "P", "X", "*"]
+
+def format_bytes(n) -> str:
+    """
+    Format size using the largest readable unit.
+
+    Examples:
+      246132K   -> 246M
+      2097148K  -> 2.0G
+
+    Notes:
+      - CSV normally gives integer bytes.
+      - This also accepts strings like "246132K" if needed.
+      - M is shown as rounded whole MB.
+      - G/T are shown with one decimal place.
+    """
+    if isinstance(n, str):
+        s = n.strip()
+        suffix = s[-1].upper()
+
+        if suffix in {"K", "M", "G", "T"}:
+            value = float(s[:-1])
+            # Interpret suffix input as decimal-style units.
+            scale = {
+                "K": 1_000,
+                "M": 1_000_000,
+                "G": 1_000_000_000,
+                "T": 1_000_000_000_000,
+            }[suffix]
+            n = int(value * scale)
+        else:
+            n = int(s)
+
+    n = int(n)
+
+    # Use G/T when the value is large enough.
+    if n >= 1024 ** 4:
+        return f"{n / (1024 ** 4):.2f}T"
+
+    if n >= 1024 ** 3:
+        return f"{n / (1024 ** 3):.2f}G"
+
+    if n >= 1_000_000:
+        return f"{round(n / 1_000_000)}M"
+
+    if n >= 1_000:
+        return f"{round(n / 1_000)}K"
+
+    return f"{n}B"
+
+def experiment_label(path: str) -> str:
+    name = Path(path).name
+
+    if name.startswith("times_") and name.endswith(".csv"):
+        return name[len("times_") : -len(".csv")]
+
+    return Path(path).stem
+
+
+def percentile(values, p: float) -> float:
+    return float(np.percentile(np.array(values, dtype=float), p))
+
+
+def read_times_csv(path: str, unit: str):
+    grouped = defaultdict(list)
+
+    with open(path, newline="") as f:
+        reader = csv.DictReader(f)
+
+        if reader.fieldnames is None:
+            raise ValueError(f"{path}: empty CSV or missing header")
+
+        fieldnames = [name.strip() for name in reader.fieldnames]
+        if fieldnames != ["bytes", "time_usec"]:
+            raise ValueError(
+                f"{path}: expected header 'bytes,time_usec', got: {','.join(fieldnames)}"
+            )
+
+        for line_no, row in enumerate(reader, start=2):
+            try:
+                nbytes = int(row["bytes"].strip())
+                time_usec = float(row["time_usec"].strip())
+            except Exception as e:
+                raise ValueError(f"{path}: invalid row at line {line_no}: {row} ({e})")
+
+            grouped[nbytes].append(time_usec * USEC_TO_UNIT[unit])
+
+    return grouped
+
+
+def add_legend_and_save(fig, ax, out_path: Path, legend_title: str, legend_outside: bool):
+    if legend_outside:
+        ax.legend(
+            title=legend_title,
+            fontsize=8,
+            loc="center left",
+            bbox_to_anchor=(1.02, 0.5),
+        )
+        fig.tight_layout(rect=[0, 0, 0.78, 1])
+    else:
+        ax.legend(title=legend_title, fontsize=8)
+        fig.tight_layout()
+
+    fig.savefig(out_path, dpi=200)
+    plt.close(fig)
+
+
+def plot_size_graph(
+    nbytes: int,
+    series,
+    unit: str,
+    out_path: Path,
+    markers_mode: str,
+    line_markers: bool,
+    legend_outside: bool,
+):
+    size_label = format_bytes(nbytes)
+    fig, ax = plt.subplots(figsize=(10, 6))
+
+    for item in series:
+        x = item["x"]
+        y = item["y"]
+        marker = item["marker"] if line_markers else None
+
+        ax.plot(
+            x,
+            y,
+            linestyle=item["linestyle"],
+            marker=marker,
+            markersize=3,
+            markevery=max(1, len(x) // 25),
+            linewidth=1.8,
+            label=f"{item['file_label']} (n={item['n']})",
+        )
+
+        if markers_mode == "tail":
+            ax.scatter([item["p90"]], [0.90], marker="x", s=70, zorder=5)
+            ax.scatter([item["p99"]], [0.99], marker="*", s=100, zorder=5)
+
+            ax.annotate(
+                "P90",
+                xy=(item["p90"], 0.90),
+                xytext=(5, 5),
+                textcoords="offset points",
+                fontsize=8,
+            )
+            ax.annotate(
+                "P99",
+                xy=(item["p99"], 0.99),
+                xytext=(5, 5),
+                textcoords="offset points",
+                fontsize=8,
+            )
+
+    ax.set_xlabel(f"Latency ({unit})")
+    ax.set_ylabel("CDF")
+    ax.set_title(f"DMA Latency CDF - {size_label}")
+    ax.grid(True)
+
+    add_legend_and_save(
+        fig,
+        ax,
+        out_path,
+        "Experiment",
+        legend_outside,
+    )
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description="Create separate latency CDF graphs per byte count from times_*.csv files."
+    )
+    parser.add_argument(
+        "inputs",
+        nargs="+",
+        help="Input CSV files with header: bytes,time_usec. Recommended naming: times_<label>.csv",
+    )
+    parser.add_argument(
+        "--unit",
+        default="usec",
+        choices=sorted(USEC_TO_UNIT.keys()),
+        help="Output time unit. Input is always time_usec. Default: usec",
+    )
+    parser.add_argument(
+        "--out",
+        default="latency_cdf.png",
+        help="Output base filename. Per-size graphs are generated from this name.",
+    )
+    parser.add_argument(
+        "--markers",
+        default="none",
+        choices=["none", "tail"],
+        help="Marker mode. 'none' disables percentile markers; 'tail' shows P90 and P99 markers. Default: none",
+    )
+    parser.add_argument(
+        "--legend-outside",
+        action="store_true",
+        help="Place legend outside the plot.",
+    )
+    parser.add_argument(
+        "--line-markers",
+        action="store_true",
+        help="Show point markers on CDF lines. Default: no line markers.",
+    )
+
+    args = parser.parse_args()
+
+    all_data = []
+
+    for path in args.inputs:
+        try:
+            grouped = read_times_csv(path, args.unit)
+        except ValueError as e:
+            print(f"ERROR: {e}", file=sys.stderr)
+            return 1
+
+        if not grouped:
+            print(f"ERROR: {path}: no data rows", file=sys.stderr)
+            return 1
+
+        all_data.append(
+            {
+                "path": path,
+                "label": experiment_label(path),
+                "grouped": grouped,
+            }
+        )
+
+    print("Latency summary")
+    print("================")
+    print(f"input_files: {len(all_data)}")
+    print(f"input_unit:  usec")
+    print(f"output_unit: {args.unit}")
+    print()
+
+    print(
+        f"{'file_label':>18} {'bytes':>14} {'size':>8} {'n':>8} "
+        f"{'min':>12} {'avg':>12} {'std':>12} "
+        f"{'p50':>12} {'p90':>12} {'p99':>12} {'max':>12}"
+    )
+
+    series_by_size = defaultdict(list)
+
+    for file_idx, item in enumerate(all_data):
+        file_label = item["label"]
+        grouped = item["grouped"]
+        linestyle = LINESTYLES[file_idx % len(LINESTYLES)]
+
+        for size_idx, nbytes in enumerate(sorted(grouped.keys())):
+            times = np.array(grouped[nbytes], dtype=float)
+            sorted_times = np.sort(times)
+            cdf = np.arange(1, len(sorted_times) + 1) / len(sorted_times)
+
+            min_v = float(np.min(times))
+            avg = float(np.mean(times))
+            std = float(np.std(times))
+            p50 = percentile(times, 50)
+            p90 = percentile(times, 90)
+            p99 = percentile(times, 99)
+            max_v = float(np.max(times))
+
+            size_label = format_bytes(nbytes)
+
+            print(
+                f"{file_label:>18} {nbytes:14d} {size_label:>8} {len(times):8d} "
+                f"{min_v:12.6f} {avg:12.6f} {std:12.6f} "
+                f"{p50:12.6f} {p90:12.6f} {p99:12.6f} {max_v:12.6f}"
+            )
+
+            series_by_size[nbytes].append(
+                {
+                    "file_label": file_label,
+                    "nbytes": nbytes,
+                    "size_label": size_label,
+                    "x": sorted_times,
+                    "y": cdf,
+                    "n": len(times),
+                    "p90": p90,
+                    "p99": p99,
+                    "linestyle": linestyle,
+                    "marker": MARKERS[size_idx % len(MARKERS)],
+                }
+            )
+
+    out_base = Path(args.out)
+    stem = out_base.stem
+    suffix = out_base.suffix or ".png"
+
+    print()
+
+    for nbytes in sorted(series_by_size.keys()):
+        size_label = format_bytes(nbytes)
+        out_path = out_base.with_name(f"{stem}_{size_label}{suffix}")
+
+        plot_size_graph(
+            nbytes=nbytes,
+            series=series_by_size[nbytes],
+            unit=args.unit,
+            out_path=out_path,
+            markers_mode=args.markers,
+            line_markers=args.line_markers,
+            legend_outside=args.legend_outside,
+        )
+
+        print(f"Wrote CDF graph: {out_path}")
+
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/decompress/bw.png b/decompress/bw.png
new file mode 100644
index 0000000..8d01e74
--- /dev/null
+++ b/decompress/bw.png
diff --git a/decompress/bw_VANILLA.csv b/decompress/bw_VANILLA.csv
new file mode 100644
index 0000000..418f2e8
--- /dev/null
+++ b/decompress/bw_VANILLA.csv
@@ -0,0 +1,751 @@
+bytes,bw_KiBps
+1073741824,3448798.624768
+1073741824,3448491.660288
+1073741824,3445689.852928
+1073741824,3442474.722304
+1073741824,3449114.630144
+1073741824,3444636.783616
+1073741824,3444600.720384
+1073741824,3447153.239040
+1073741824,3446643.912704
+1073741824,3447379.062784
+1073741824,3444459.552768
+1073741824,3441856.836608
+1073741824,3451319.576576
+1073741824,3443677.060096
+1073741824,3446698.179584
+1073741824,3446929.281024
+1073741824,3446003.601408
+1073741824,3446155.881472
+1073741824,3444572.578816
+1073741824,3447942.255616
+1073741824,3446527.760384
+1073741824,3446319.808512
+1073741824,3444942.101504
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diff --git a/decompress/bw_all.CSV b/decompress/bw_all.CSV
new file mode 100644
index 0000000..c025bfe
--- /dev/null
+++ b/decompress/bw_all.CSV
@@ -0,0 +1,4 @@
+bytes,size,VANILLA,VANILLA_err,FALCO,FALCO_err,TETRA,TETRA_err,TRACE,TRACE_err
+268435456,256M,3371.312850,6.685594,,,,,,
+536870912,512M,3367.953428,4.529973,,,,,,
+1073741824,1G,3365.289682,2.809557,,,,,,
diff --git a/decompress/combine.py b/decompress/combine.py
new file mode 100755
index 0000000..7397449
--- /dev/null
+++ b/decompress/combine.py
@@ -0,0 +1,169 @@
+#!/usr/bin/env python3
+
+import csv
+import glob
+import math
+from collections import defaultdict
+from pathlib import Path
+
+
+LABELS = ["VANILLA", "FALCO", "TETRA", "TRACE"]
+
+
+def label_from_path(path: str, prefix: str) -> str:
+    stem = Path(path).stem
+    if stem.startswith(prefix):
+        stem = stem[len(prefix):]
+    return stem.upper()
+
+
+def format_size(n: int) -> str:
+    gib = 1024 ** 3
+    mib = 1024 ** 2
+    kib = 1024
+
+    if n >= gib:
+        v = n / gib
+        if abs(v - round(v)) < 0.03:
+            return f"{int(round(v))}G"
+        return f"{v:.1f}G"
+
+    if n >= mib:
+        v = n / mib
+        if abs(v - round(v)) < 0.03:
+            return f"{int(round(v))}M"
+        return f"{round(n / 1_000_000)}M"
+
+    if n >= kib:
+        return f"{round(n / 1000)}K"
+
+    return f"{n}B"
+
+
+def mean(xs):
+    return sum(xs) / len(xs)
+
+
+def stddev(xs):
+    m = mean(xs)
+    return math.sqrt(sum((x - m) ** 2 for x in xs) / len(xs))
+
+
+def prepare_times():
+    groups = defaultdict(list)
+
+    for path in sorted(glob.glob("times_*.csv")):
+        label = label_from_path(path, "times_")
+
+        if label not in LABELS:
+            print(f"Skipping unknown latency label: {path}")
+            continue
+
+        with open(path, newline="") as f:
+            r = csv.DictReader(f)
+            if r.fieldnames != ["bytes", "time_usec"]:
+                raise ValueError(f"{path}: expected bytes,time_usec, got {r.fieldnames}")
+
+            for row in r:
+                nbytes = int(row["bytes"])
+                time_usec = float(row["time_usec"])
+                groups[(label, nbytes)].append(time_usec)
+
+    sizes = sorted({nbytes for (_, nbytes) in groups.keys()})
+
+    fieldnames = ["bytes"]
+    for label in LABELS:
+        fieldnames += [f"{label}_time_usec", f"{label}_cdf"]
+
+    with open("times_all.CSV", "w", newline="") as f:
+        w = csv.DictWriter(f, fieldnames=fieldnames)
+        w.writeheader()
+
+        for nbytes in sizes:
+            per_label = {}
+            max_n = 0
+
+            for label in LABELS:
+                values = sorted(groups.get((label, nbytes), []))
+                n = len(values)
+                max_n = max(max_n, n)
+
+                per_label[label] = [
+                    (v, (i + 1) / n) for i, v in enumerate(values)
+                ] if n else []
+
+            for i in range(max_n):
+                row = {"bytes": nbytes}
+
+                for label in LABELS:
+                    if i < len(per_label[label]):
+                        t, cdf = per_label[label][i]
+                        row[f"{label}_time_usec"] = f"{t / 1000.0:.6f}"
+                        row[f"{label}_cdf"] = f"{cdf:.9f}"
+                    else:
+                        row[f"{label}_time_usec"] = ""
+                        row[f"{label}_cdf"] = ""
+
+                w.writerow(row)
+
+    print("Wrote times_all.CSV")
+
+
+def prepare_bw():
+    groups = defaultdict(list)
+
+    for path in sorted(glob.glob("bw_*.csv")):
+        label = label_from_path(path, "bw_")
+
+        if label not in LABELS:
+            print(f"Skipping unknown bandwidth label: {path}")
+            continue
+
+        with open(path, newline="") as f:
+            r = csv.DictReader(f)
+            if r.fieldnames != ["bytes", "bw_KiBps"]:
+                raise ValueError(f"{path}: expected bytes,bw_KiBps, got {r.fieldnames}")
+
+            for row in r:
+                nbytes = int(row["bytes"])
+                bw_mibps = float(row["bw_KiBps"]) / 1024.0
+                groups[(label, nbytes)].append(bw_mibps)
+
+    sizes = sorted({nbytes for (_, nbytes) in groups.keys()})
+
+    fieldnames = ["bytes", "size"]
+    for label in LABELS:
+        fieldnames += [label, f"{label}_err"]
+
+    with open("bw_all.CSV", "w", newline="") as f:
+        w = csv.DictWriter(f, fieldnames=fieldnames)
+        w.writeheader()
+
+        for nbytes in sizes:
+            row = {
+                "bytes": nbytes,
+                "size": format_size(nbytes),
+            }
+
+            for label in LABELS:
+                values = groups.get((label, nbytes), [])
+
+                if values:
+                    row[label] = f"{mean(values):.6f}"
+                    row[f"{label}_err"] = f"{stddev(values):.6f}"
+                else:
+                    row[label] = ""
+                    row[f"{label}_err"] = ""
+
+            w.writerow(row)
+
+    print("Wrote bw_all.CSV")
+
+
+def main():
+    prepare_times()
+    prepare_bw()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/decompress/run.sh b/decompress/run.sh
new file mode 100755
index 0000000..e75b465
--- /dev/null
+++ b/decompress/run.sh
@@ -0,0 +1,150 @@
+#!/usr/bin/env bash
+
+set -euo pipefail
+
+usage() {
+    echo "Usage: $0 <tag> <runs> <remote-chunk-directory> <chunk-size> [remote-log-prefix-base]"
+    echo
+    echo "Examples:"
+    echo "  $0 VANILLA_1G 10 bins/1G 1M"
+    echo "  $0 TRACE_5G   10 bins/5G 1M TRACE_5G"
+}
+
+if [[ $# -lt 4 || $# -gt 5 ]]; then
+    usage
+    exit 1
+fi
+
+TAG="$1"
+RUNS="$2"
+REMOTE_CHUNK_DIR="$3"
+CHUNK_SIZE="$4"
+REMOTE_PREFIX_BASE="${5:-${TAG}}"
+
+SSH_KEY="$HOME/.ssh/id_ed25519"
+REMOTE_HOST="ubuntu@143.248.53.46"
+REMOTE_DIR="/home/ubuntu/siho-benchmark/compress"
+
+# DPU-side PCI BDF.
+DPU_PCI="03:00.0"
+
+# DPU-side wrapper script.
+DPU_SCRIPT="./run.sh"
+
+TIMES_CSV="times_${TAG}.csv"
+BW_CSV="bw_${TAG}.csv"
+
+SSH_OPTS=(
+    -i "$SSH_KEY"
+    -n
+    -o BatchMode=yes
+    -o StrictHostKeyChecking=accept-new
+)
+
+echo "====="
+echo "SIHO'S DOCA DECOMPRESS BENCHMARKING"
+echo "SSH KEY LOCATION: $SSH_KEY"
+echo "REMOTE HOST: $REMOTE_HOST"
+echo "REMOTE DIR: $REMOTE_DIR"
+echo "TAG: $TAG"
+echo "DPU PCIE ADDRESS: $DPU_PCI"
+echo "RUNS: $RUNS"
+echo "REMOTE CHUNK DIR: $REMOTE_CHUNK_DIR"
+echo "CHUNK SIZE: $CHUNK_SIZE"
+echo "DPU SCRIPT: $DPU_SCRIPT"
+echo "====="
+echo "PROCEED (y/N)?"
+
+read -r proceed
+
+if [[ "${proceed:-}" != "y" ]]; then
+    echo "TERMINATING..."
+    exit 0
+fi
+
+for i in $(seq 1 "$RUNS"); do
+    echo "===== RUN $i/$RUNS ====="
+
+    RUN_LABEL="${REMOTE_PREFIX_BASE}_run_${i}"
+
+    echo "[dpu] Running decompressor through wrapper..."
+
+    if ! dpu_out="$(
+        ssh "${SSH_OPTS[@]}" "$REMOTE_HOST" \
+            "cd '$REMOTE_DIR' && sudo -n '$DPU_SCRIPT' '$REMOTE_PREFIX_BASE' '$DPU_PCI' '$REMOTE_CHUNK_DIR' '$CHUNK_SIZE' '$RUN_LABEL'" \
+            2>&1
+    )"; then
+        echo "ERROR: DPU decompressor failed"
+        echo "$dpu_out"
+        exit 1
+    fi
+
+    compressed_bytes="$(
+        awk '/^[[:space:]]*compressed_bytes:/ {print $2}' <<< "$dpu_out" | tail -n1
+    )"
+
+    bytes="$(
+        awk '/^[[:space:]]*bytes:/ {print $2}' <<< "$dpu_out" | tail -n1
+    )"
+
+    time_val="$(
+        awk '/^[[:space:]]*time:/ {print $2}' <<< "$dpu_out" | tail -n1
+    )"
+
+    time_unit="$(
+        awk '/^[[:space:]]*time:/ {print $3}' <<< "$dpu_out" | tail -n1
+    )"
+
+    bw_val="$(
+        awk '/^[[:space:]]*BW:/ {print $2}' <<< "$dpu_out" | tail -n1
+    )"
+
+    bw_unit="$(
+        awk '/^[[:space:]]*BW:/ {print $3}' <<< "$dpu_out" | tail -n1
+    )"
+
+    chunks="$(
+        awk '/^[[:space:]]*chunks:/ {print $2}' <<< "$dpu_out" | tail -n1
+    )"
+
+    if [[ -z "${bytes:-}" || -z "${time_val:-}" || -z "${bw_val:-}" ]]; then
+        echo "ERROR: failed to parse DPU output"
+        echo "$dpu_out"
+        exit 1
+    fi
+
+    # Convert time to usec.
+    case "$time_unit" in
+    usec) time_usec="$time_val" ;;
+    msec) time_usec="$(awk -v x="$time_val" 'BEGIN { printf "%.6f", x * 1000.0 }')" ;;
+    sec)  time_usec="$(awk -v x="$time_val" 'BEGIN { printf "%.6f", x * 1000000.0 }')" ;;
+    nsec) time_usec="$(awk -v x="$time_val" 'BEGIN { printf "%.6f", x / 1000.0 }')" ;;
+    *)    time_usec="$time_val" ;;
+    esac
+
+    # Convert bandwidth to KiB/s.
+    case "$bw_unit" in
+    KiB/s|KiBps) bw_kibps="$bw_val" ;;
+    MiB/s|MiBps) bw_kibps="$(awk -v x="$bw_val" 'BEGIN { printf "%.6f", x * 1024.0 }')" ;;
+    GiB/s|GiBps) bw_kibps="$(awk -v x="$bw_val" 'BEGIN { printf "%.6f", x * 1024.0 * 1024.0 }')" ;;
+    B/s|Bps)     bw_kibps="$(awk -v x="$bw_val" 'BEGIN { printf "%.6f", x / 1024.0 }')" ;;
+    *)           bw_kibps="$bw_val" ;;
+    esac
+
+    if [[ ! -f "$TIMES_CSV" ]]; then
+        echo "bytes,time_usec" > "$TIMES_CSV"
+    fi
+
+    if [[ ! -f "$BW_CSV" ]]; then
+        echo "bytes,bw_KiBps" > "$BW_CSV"
+    fi
+
+    echo "$bytes,$time_usec" >> "$TIMES_CSV"
+    echo "$bytes,$bw_kibps" >> "$BW_CSV"
+
+    echo "[result] chunks=${chunks:-N/A} compressed_bytes=${compressed_bytes:-N/A} bytes=$bytes time_usec=$time_usec bw_KiBps=$bw_kibps"
+    echo "===== RUN $i/$RUNS DONE ====="
+done
+
+echo "Wrote: $TIMES_CSV"
+echo "Wrote: $BW_CSV"
diff --git a/decompress/sum.sh b/decompress/sum.sh
new file mode 100755
index 0000000..1958da7
--- /dev/null
+++ b/decompress/sum.sh
@@ -0,0 +1,21 @@
+#!/bin/bash
+
+set -euo pipefail
+
+	#times_FALCO.csv \
+	#times_TETRA.csv \
+	#times_TRACE.csv \
+	#bw_FALCO.csv \
+	#bw_TETRA.csv \
+	#bw_TRACE.csv \
+
+./analyze_time.py \
+	--unit msec \
+	--out time \
+	times_VANILLA.csv \
+       	| tee ./summary/times.txt
+./analyze_bw.py \
+	--unit MiBps \
+	--out bw \
+	bw_VANILLA.csv \
+	| tee ./summary/bw.txt
diff --git a/decompress/summary/bw.txt b/decompress/summary/bw.txt
new file mode 100644
index 0000000..f1b25a2
--- /dev/null
+++ b/decompress/summary/bw.txt
@@ -0,0 +1,12 @@
+Bandwidth summary
+=================
+input_files: 1
+input_unit:  KiB/s
+output_unit: MiB/s
+
+        file_label          bytes     size        n          min          avg          std           p1           p5          p10          p50          p90          p99          max
+           VANILLA      268435456     268M      250  3344.548982  3371.312850     6.685594  3347.701525  3361.129544  3364.969564  3371.066053  3379.927964  3383.944785  3384.814959
+           VANILLA      536870912     537M      250  3348.809017  3367.953428     4.529973  3354.894507  3361.489498  3363.155884  3367.992598  3373.710145  3379.271457  3380.398829
+           VANILLA     1073741824    1.00G      250  3355.466436  3365.289682     2.809557  3360.016221  3361.190035  3362.109871  3364.983041  3368.781319  3373.685582  3374.027910
+
+Wrote bar graph: bw
diff --git a/decompress/summary/times.txt b/decompress/summary/times.txt
new file mode 100644
index 0000000..bddaed3
--- /dev/null
+++ b/decompress/summary/times.txt
@@ -0,0 +1,14 @@
+Latency summary
+================
+input_files: 1
+input_unit:  usec
+output_unit: msec
+
+        file_label          bytes     size        n          min          avg          std          p50          p90          p99          max
+           VANILLA      268435456     268M      250    75.631904    75.935109     0.150845    75.940369    76.077954    76.470390    76.542458
+           VANILLA      536870912     537M      250   151.461418   152.021380     0.204555   152.019337   152.237963   152.612848   152.890176
+           VANILLA     1073741824    1.00G      250   303.494822   304.283081     0.253941   304.310597   304.570653   304.760434   305.173668
+
+Wrote CDF graph: time_268M.png
+Wrote CDF graph: time_537M.png
+Wrote CDF graph: time_1.00G.png
diff --git a/decompress/time_1.00G.png b/decompress/time_1.00G.png
new file mode 100644
index 0000000..48ea6be
--- /dev/null
+++ b/decompress/time_1.00G.png
diff --git a/decompress/time_268M.png b/decompress/time_268M.png
new file mode 100644
index 0000000..9f6c7f5
--- /dev/null
+++ b/decompress/time_268M.png
diff --git a/decompress/time_537M.png b/decompress/time_537M.png
new file mode 100644
index 0000000..baed4d3
--- /dev/null
+++ b/decompress/time_537M.png
diff --git a/decompress/times_VANILLA.csv b/decompress/times_VANILLA.csv
new file mode 100644
index 0000000..94b7098
--- /dev/null
+++ b/decompress/times_VANILLA.csv
@@ -0,0 +1,751 @@
+bytes,time_usec
+1073741824,304040.947
+1073741824,304068.011
+1073741824,304315.259
+1073741824,304599.477
+1073741824,304013.091
+1073741824,304408.292
+1073741824,304411.479
+1073741824,304186.071
+1073741824,304231.022
+1073741824,304166.145
+1073741824,304423.955
+1073741824,304654.159
+1073741824,303818.866
+1073741824,304493.128
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diff --git a/decompress/times_all.CSV b/decompress/times_all.CSV
new file mode 100644
index 0000000..1c08448
--- /dev/null
+++ b/decompress/times_all.CSV
@@ -0,0 +1,751 @@
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