Computational species "bw filter simplified less" (CID=45741e3fbcf4024b:1db78910464c9d05)

Notes

Some cost-aware experiments (execution time, size, energy, compilation time) performed by Grigori Fursin. It supports our research on continuous performance tracking, code optimization and compiler benchmarking (regression detection).

This computation species (kernel) is a threshold filter - it is used in image processing and neuron activation functions (part of artificial neural networks).

Used artifacts

• Datasets:
  • D1 = image raw fgg office day gray (CID=8a7141c59cd335f5:c8848a1b1fb1775e), size=1536x1536~2.4E6 (pixels or neurons)
  • D2 = image raw fgg office night gray (CID=8a7141c59cd335f5:0045c9b59e84318b), size=1536x1536~2.4E6

• Systems:
  • S1 = Dell Laptop Latitude E6320, Processor=P1, Memory = 8Gb, Storage=256Gb (SSD), Max power consumption=52W, Cost=800 euro (CID=cb7e6b406491a11c:0d84339816de0271)
  • S2 = Samsung Mobile Galaxy Duos GT-S6312, Processor=P2, Memory = 0.8Gb, Storage=4Gb, Battery=1300 mAh / 3.9V / up to 250 hours, Max power consumption~5W, Cost=120 euro (CID=cb7e6b406491a11c:a9740acbe06bcd1e)
  • S3 = Polaroid Tablet Executive 9", Processor=P3, Memory=1Gb, Storage=16Gb, Battery=3500 mAh / 3.9V / up to 80 hours, Max power consumption~, Cost=80 euro ()

• Processors:
  • P1 = Intel Core i5-2540M, 2.60GHz, 2 cores (CID=54cd38490124ef51:425ae4e3483c82e8)
  • P2 = Qualcomm MSM7625A FFA, ARM Cortex A5, ARMv7, 1 GHz, 1 core (CID=54cd38490124ef51:ae17889f40209ae7)
  • P3 =
• Processor mode:
  • B1 = 32 bit
  • B2 = 64 bit

• OSs:
  • O1 = Windows 7 Pro SP1 (CID=c4d3ce728f46eea2:10c4f7484446b689)
  • O2 = OpenSuse 12.1, Kernel 3.1.10 (CID=c4d3ce728f46eea2:29ce89f1a1446e89)
  • O3 = Android 4.1.2, Kernel 3.4.0 (CID=c4d3ce728f46eea2:e734c48d5a5824c1)
  • O4 = Android 4.

• Compilers:
  • LLVMXYZ = LLVM X.Y.Z
  • GCCXYZ = GCC X.Y.Z
  • MGCCXYZ = MingW X.Y.Z
  • SGCCXYZ = Sourcergy GCC X.Y.Z. for ARM
  • MX = Microsoft Visual Studio compilers X
  • IX = Intel X

• Number of run-time code repetitions (for example, processing steps in neural networks):
  • R1 = 4000
  • R2 = 1000
  • R3 = 400
• Total number of computations (processed neurons or pixels)
  • T1 ~ 9.6E9
  • T2 ~ 2.4E9
  • T3 ~ 1.0E9

Notes

Energy: 1Wh = 3600 joules

W = mAh * V / 1000 = 1300 * 3.9 / 1000 ~ 5W