Science Mark 2.0 Beta 17112002
Author:
sciencemark.org
Date: 12/05/2002 Size: 281 KB License: Freeware Requires: Win 10 / 8 / 7 / Vista / XP Downloads: 44229 times TIP: Click Here to Repair or Restore Missing Windows Files |
Science Mark is a suite of benchmarks that realistically stress system performance. Project has been abandoned.
Science Mark is an attempt to put the truth behind benchmarking. In an attempt to model real-world demands and performance, SM2 is a suite of high-performance benchmarks that realistically stress system performance without architectural bias.
The benchmarks in wide use today fail to reflect system performance due to the following accurately:
1. Relevance: The benchmarks test only one application and don't address a wider array of
applications more representative of the user's market.
2. Abstraction: They are entirely comprised of synthetic tasks that don't perform a complex, meaningful task.
3. Quality: May be poorly constructed from a C or Fortran perspective and limited in their ability to measure the true potential of a system.
4.Objectivity: The test is developed on or tuned for one architecture resulting in implicit performance bias.
Synthetic benchmarks are useful and can tell the user valuable performance characteristics about their system's performance, but they should not be used in entirety to measure system performance; this role is reserved in greater part to real applications performing real tasks. Science Mark 2.0 is comprised of 7 benchmarks, each of which measures a different aspect of real-world system performance.
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Science Mark is an attempt to put the truth behind benchmarking. In an attempt to model real-world demands and performance, SM2 is a suite of high-performance benchmarks that realistically stress system performance without architectural bias.
The benchmarks in wide use today fail to reflect system performance due to the following accurately:
1. Relevance: The benchmarks test only one application and don't address a wider array of
applications more representative of the user's market.
2. Abstraction: They are entirely comprised of synthetic tasks that don't perform a complex, meaningful task.
3. Quality: May be poorly constructed from a C or Fortran perspective and limited in their ability to measure the true potential of a system.
4.Objectivity: The test is developed on or tuned for one architecture resulting in implicit performance bias.
Synthetic benchmarks are useful and can tell the user valuable performance characteristics about their system's performance, but they should not be used in entirety to measure system performance; this role is reserved in greater part to real applications performing real tasks. Science Mark 2.0 is comprised of 7 benchmarks, each of which measures a different aspect of real-world system performance.
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Screenshot for Science Mark