Abstract: A system and methods for capacity planning of electronic systems storage are provided. Features include a non-invasive data discovery and collection mechanism, an adaptive grouping mechanism, a flexible analysis mechanism, predictive modeling and forecasting mechanisms, and a business metric and correlation mechanism. A discovery engine that ascertains the availability of collectable entities. A collection engine in turn gathers information from and about entities discovered by the discovery engine. A grouping module groups together entities according to parameters specified by the user. An analysis and forecasting module allows a user to create, modify and save forecast scenarios from which a model is generated by a modeling module. Correlations can be identified between specified key business metrics and historical data. Once a model has been created, a forecast is generated and can then be analyzed using Bold Freehand Extrapolation, time-series analysis, and business trend-based forecasting.

Abstract: A system and methods for capacity planning of electronic systems storage are provided. Features include a non-invasive data discovery and collection mechanism, an adaptive grouping mechanism, a flexible analysis mechanism, predictive modeling and forecasting mechanisms, and a business metric and correlation mechanism. A discovery engine that ascertains the availability of collectable entities. A collection engine in turn gathers information from and about entities discovered by the discovery engine. A grouping module groups together entities according to parameters specified by the user. An analysis and forecasting module allows a user to create, modify and save forecast scenarios from which a model is generated by a modeling module. Correlations can be identified between specified key business metrics and historical data. Once a model has been created, a forecast is generated and can then be analyzed using Bold Freehand Extrapolation, time-series analysis, and business trend-based forecasting.

Abstract: A streamlined technique for obtaining interpolated color output values from corresponding color input values based on color output values stored in a color look-up table, with tetrahedral interpolation being applied so as to dissect each cubic grid of the color look-up table into plural tetrahedrons. According to the invention, processing efficiency is increased by avoiding the use of conditional branches when making a determination as to which of the plural dissected tetrahedrons a particular color input value falls. Preferably, rather than making such a determination, weights for all possible tetrahedrons for one cube are stored in a temporary look-up table, and an index into the temporary look-up table is calculated based on the magnitude of component values for each color input value. The index is calculated in a block of code that does not include conditional branches that are conditioned on the relative magnitude of the component values of the color input value.

Abstract: A streamlined technique for obtaining interpolated color output values from corresponding color input values based on color output values stored in a color look-up table, with tetrahedral interpolation being applied so as to dissect each cubic grid of the color look-up table into plural tetrahedrons. According to the invention, processing efficiency is increased by avoiding the use of conditional branches when making a determination as to which of the plural dissected tetrahedrons a particular color input value falls. Preferably, rather than making such a determination, weights for all possible tetrahedrons for one cube are stored in a temporary look-up table, and an index into the temporary look-up table is calculated based on the magnitude of component values for each color input value. The index is calculated in a block of code that does not include conditional branches that are conditioned on the relative magnitude of the component values of the color input value.