streaming

.github/workflows/cmake.yml

@@ -48,4 +48,5 @@ jobs:
           ./sketch_test "--success"
           ./crs_test "--success"
           ./weighted_cr_test "--success"
-          ./block_partition_test "--success"
+          ./block_partition_test "--success"
+          ./streaming_test "--success"

CMakeLists.txt

@@ -90,4 +90,8 @@ install(DIRECTORY "include" DESTINATION "/IntelliStream" COMPONENT IntelliStream
 file(GLOB allCopyFiles "${PROJECT_SOURCE_DIR}/scripts/*")
 file(COPY ${allCopyFiles} DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/benchmark/scripts)
 file(COPY ${allCopyFiles} DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/benchmark/scripts)
-#file(COPY ${allCopyFiles} DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/scripts)
+
+# copy files needed for real world matrix loader
+set(source_directory "${CMAKE_SOURCE_DIR}/benchmark/datasets/")
+set(destination_directory "${CMAKE_BINARY_DIR}/benchmark/datasets/")
+file(COPY ${source_directory} DESTINATION ${destination_directory})

README.md

@@ -217,5 +217,6 @@ You will find the figures then.
    to validate the highlight when you need it, and comment it during a compile. :)
 4. When setting up torch for cpu under python version > 3.10, torch == 1.13.0 would conflict with torchaudio according
    to https://pytorch.org/audio/stable/installation.html. Use Python version <= 3.10 for smooth installation.
-5. Some heavy-weight algos like co-occurring FD may be treated as a zombie thread by some OS like ubuntu if running in default benchmark program, in this case
-, please force them to be executed as a running child thread by setting forceMP(U64)=1 and threads(U64)=1 in config
+5. Some heavy-weight algos like co-occurring FD may be treated as a zombie thread by some OS like ubuntu if running in
+   default benchmark program, in this case
+   , please force them to be executed as a running child thread by setting forceMP(U64)=1 and threads(U64)=1 in config

benchmark/CMakeLists.txt

@@ -18,6 +18,8 @@ if (BUILD_BENCHMARKS)
     include_directories("include/")
     add_executable(benchmark "src/Benchmark.cpp")
     target_link_libraries(benchmark IntelliStream)
+    add_executable(benchmarkPCA "src/BenchmarkPCA.cpp")
+    target_link_libraries(benchmarkPCA IntelliStream)
 
     file(COPY ${CMAKE_CURRENT_SOURCE_DIR}/scripts
             DESTINATION ${CMAKE_CURRENT_BINARY_DIR})
@@ -27,6 +29,10 @@ if (BUILD_BENCHMARKS)
             DESTINATION ${CMAKE_CURRENT_BINARY_DIR})
     file(COPY ${CMAKE_CURRENT_SOURCE_DIR}/config.csv
             DESTINATION ${CMAKE_CURRENT_BINARY_DIR})
+
+    set_target_properties(benchmarkPCA PROPERTIES RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/scripts/PCA)
+
+
     file(COPY ${PROJECT_SOURCE_DIR}/src/CL
             DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/)
     message("---Done building benchmarks")

benchmark/pythonTest.py

@@ -5,18 +5,18 @@ def main():
     # load the library, assume it is located together with this file
     torch.ops.load_library("../libIntelliStream.so")
     # gen the input tensor
-    a = torch.randn(2, 10)
-    b = torch.randn(2, 10)
+    a = torch.rand(100, 100)
+    b = torch.rand(100, 100)
     # The pytorch +
     print('/****test add****/')
-    print('pytorch+:', a + b)
+    print('pytorch-mm:', torch.matmul(a,b))
     # our c++ extension of +
-    print('myLib+:', torch.ops.myLib.myVecAdd(a, b))
-    # The pytorch -
-    print('/****test sub****/')
-    print('pytorch-:', a - b)
-    # our c++ extension of -
-    print('myLib-:', torch.ops.myLib.myVecSub(a, b))
+    torch.ops.load_library("../libIntelliStream.so")
+    torch.ops.AMMBench.setTag('mm')
+    print('AMMBench-MM+:', torch.ops.AMMBench.ammDefault(a, b))
+    torch.ops.AMMBench.setTag('crs')
+    print('AMMBench-CRS+:', torch.ops.AMMBench.ammDefault(a, b))
+
 
 
 if __name__ == "__main__":

benchmark/scripts/PCA/preprocess.ipynb

@@ -0,0 +1,73 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import glob\n",
+    "import sys\n",
+    "sys.path.append('/home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/benchmark/scripts/PCA/scanSketchSize_SIFT')\n",
+    "from OoOCommon import *"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Change aRow, aCol, bCol in config file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for csv in glob.glob('/home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/benchmark/scripts/PCA/scanSketchSize_100000*1000*100000/config*.csv'):\n",
+    "    aRow = csv.split('/')[-2].split('_')[1].split('*')[0]\n",
+    "    aCol = csv.split('/')[-2].split('_')[1].split('*')[1]\n",
+    "    bCol = csv.split('/')[-2].split('_')[1].split('*')[2]\n",
+    "    editConfig(csv, csv, 'aRow', aRow)\n",
+    "    editConfig(csv, csv, 'aCol', aCol)\n",
+    "    editConfig(csv, csv, 'bCol', bCol)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

benchmark/scripts/PCA/run.sh

@@ -0,0 +1,34 @@
+cd /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/scanSketchSize_SIFT
+python3 drawTogether.py
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension_SIFT
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension_SIFT
+
+cd /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/scanSketchSize_100*10000*100
+python3 drawTogether.py
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension_100*10000*100
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension_100*10000*100
+
+cd /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/scanSketchSize_1000*1000*1000
+python3 drawTogether.py
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension_1000*1000*1000
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension_1000*1000*1000
+
+cd /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/scanSketchSize_10000*100*10000
+python3 drawTogether.py
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension_10000*100*10000
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension_10000*100*10000
+
+cd /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/scanSketchSize_1000*100000*1000
+python3 drawTogether.py
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension_1000*100000*1000
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension_1000*100000*1000
+
+cd /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/scanSketchSize_10000*10000*10000
+python3 drawTogether.py
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension_10000*10000*10000
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension_10000*10000*10000
+
+cd /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/scanSketchSize_100000*1000*100000
+python3 drawTogether.py
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/figures/sketchDimension_100000*1000*100000
+mv /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension /home/yuhao/Documents/work/SUTD/AMM/codespace/AMMBench/build/benchmark/scripts/PCA/results/sketchDimension_100000*1000*100000

benchmark/scripts/PCA/scanSketchSize_100*10000*100/OoOCommon.py

@@ -0,0 +1,125 @@
+import csv
+import numpy as np
+import matplotlib.pyplot as plt
+import itertools as it
+import os
+
+import matplotlib
+import matplotlib.pyplot as plt
+import numpy as np
+import pylab
+from matplotlib.font_manager import FontProperties
+from matplotlib.ticker import LogLocator, LinearLocator
+import os
+import pandas as pd
+import sys
+import matplotlib.ticker as mtick
+
+OPT_FONT_NAME = 'Helvetica'
+TICK_FONT_SIZE = 22
+LABEL_FONT_SIZE = 28
+LEGEND_FONT_SIZE = 30
+LABEL_FP = FontProperties(style='normal', size=LABEL_FONT_SIZE)
+LEGEND_FP = FontProperties(style='normal', size=LEGEND_FONT_SIZE)
+TICK_FP = FontProperties(style='normal', size=TICK_FONT_SIZE)
+
+MARKERS = (['*', '|', 'v', "^", "", "h", "<", ">", "+", "d", "<", "|", "", "+", "_"])
+# you may want to change the color map for different figures
+COLOR_MAP = (
+    '#B03A2E', '#2874A6', '#239B56', '#7D3C98', '#FFFFFF', '#F1C40F', '#F5CBA7', '#82E0AA', '#AEB6BF', '#AA4499')
+# you may want to change the patterns for different figures
+PATTERNS = (["////", "o", "", "||", "-", "//", "\\", "o", "O", "////", ".", "|||", "o", "---", "+", "\\\\", "*"])
+LABEL_WEIGHT = 'bold'
+LINE_COLORS = COLOR_MAP
+LINE_WIDTH = 3.0
+MARKER_SIZE = 15.0
+MARKER_FREQUENCY = 1000
+
+
+def editConfig(src, dest, key, value):
+    df = pd.read_csv(src, header=None)
+    rowIdx = 0
+    idxt = 0
+    for cell in df[0]:
+        # print(cell)
+        if (cell == key):
+            rowIdx = idxt
+            break
+        idxt = idxt + 1
+    df[1][rowIdx] = str(value)
+    df.to_csv(dest, index=False, header=False)
+
+
+def readConfig(src, key):
+    df = pd.read_csv(src, header=None)
+    rowIdx = 0
+    idxt = 0
+    for cell in df[0]:
+        # print(cell)
+        if (cell == key):
+            rowIdx = idxt
+            break
+        idxt = idxt + 1
+    return df[1][rowIdx]
+
+
+def draw2yLine(NAME, Com, R1, R2, l1, l2, m1, m2, fname):
+    fig, ax1 = plt.subplots(figsize=(10, 6.4))
+    lines = [None] * 2
+    # ax1.set_ylim(0, 1)
+    print(Com)
+    print(R1)
+    lines[0], = ax1.plot(Com, R1, color=LINE_COLORS[0], \
+                         linewidth=LINE_WIDTH, marker=MARKERS[0], \
+                         markersize=MARKER_SIZE
+                         #
+                         )
+
+    # plt.show()
+    ax1.set_ylabel(m1, fontproperties=LABEL_FP)
+    ax1.set_xlabel(NAME, fontproperties=LABEL_FP)
+    # ax1.set_xticklabels(ax1.get_xticklabels())  # 设置共用的x轴
+    plt.xticks(rotation=0, size=TICK_FONT_SIZE)
+    plt.yticks(rotation=0, size=TICK_FONT_SIZE)
+    plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号
+    ax2 = ax1.twinx()
+
+    # ax2.set_ylabel('latency/us')
+    # ax2.set_ylim(0, 0.5)
+    lines[1], = ax2.plot(Com, R2, color=LINE_COLORS[1], \
+                         linewidth=LINE_WIDTH, marker=MARKERS[1], \
+                         markersize=MARKER_SIZE)
+
+    ax2.set_ylabel(m2, fontproperties=LABEL_FP)
+    # ax2.vlines(192000, min(R2)-1, max(R2)+1, colors = "GREEN", linestyles = "dashed",label='total L1 size')
+    # plt.grid(axis='y', color='gray')
+
+    # style = dict(size=10, color='black')
+    # ax2.hlines(tset, 0, x2_list[len(x2_list)-1]+width, colors = "r", linestyles = "dashed",label="tset")
+    # ax2.text(4, tset, "$T_{set}$="+str(tset)+"us", ha='right', **style)
+
+    # plt.xlabel('batch', fontproperties=LABEL_FP)
+
+    # plt.xscale('log')
+    # figure.xaxis.set_major_locator(LinearLocator(5))
+    ax1.yaxis.set_major_locator(LinearLocator(5))
+    ax2.yaxis.set_major_locator(LinearLocator(5))
+    ax1.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1f'))
+    ax2.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1f'))
+    ax1.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1f'))
+    ax2.yaxis.set_major_formatter(mtick.FormatStrFormatter('%.1f'))
+    plt.legend(lines,
+               [l1, l2],
+               prop=LEGEND_FP,
+               loc='upper center',
+               ncol=1,
+               bbox_to_anchor=(0.55, 1.3
+                               ), shadow=False,
+               columnspacing=0.1,
+               frameon=True, borderaxespad=-1.5, handlelength=1.2,
+               handletextpad=0.1,
+               labelspacing=0.1)
+    plt.yticks(rotation=0, size=TICK_FONT_SIZE)
+    plt.tight_layout()
+
+    plt.savefig(fname + ".pdf")