Abstract: A method for capturing hydrocarbons from a formation is provided. After a first hydraulic fracturing of a formation to produce a first conditioned formation, and while hydrocarbons are being produced from the first conditioned formation, a predetermined wellbore characteristic is monitored for. The predetermined wellbore characteristic is based on at least a pressure within the first conditioned formation. After detecting the predetermined wellbore characteristic, a second hydraulic fracturing of the formation is effected to produce a second conditioned formation.

Abstract: A method for capturing hydrocarbons from a formation is provided. After a first hydraulic fracturing of a formation to produce a first conditioned formation, and while hydrocarbons are being produced from the first conditioned formation, a predetermined wellbore characteristic is monitored for. The predetermined wellbore characteristic is based on at least a pressure within the first conditioned formation. After detecting the predetermined wellbore characteristic, a second hydraulic fracturing of the formation is effected to produce a second conditioned formation.

Abstract: The present invention, known as runspace, relates to the field of computing system management, data processing and data communications, and specifically to synergistic methods and systems which provide resource-efficient computation, especially for decomposable many-component tasks executable on multiple processing elements, by using a metric space representation of code and data locality to direct allocation and migration of code and data, by performing analysis to mark code areas that provide opportunities for runtime improvement, and by providing a low-power, local, secure memory management system suitable for distributed invocation of compact sections of code accessing local memory. Runspace provides mechanisms supporting hierarchical allocation, optimization, monitoring and control, and supporting resilient, energy efficient large-scale computing.

Abstract: The present invention, known as runspace, relates to the field of computing system management, data processing and data communications, and specifically to synergistic methods and systems which provide resource-efficient computation, especially for decomposable many-component tasks executable on multiple processing elements, by using a metric space representation of code and data locality to direct allocation and migration of code and data, by performing analysis to mark code areas that provide opportunities for runtime improvement, and by providing a low-power, local, secure memory management system suitable for distributed invocation of compact sections of code accessing local memory. Runspace provides mechanisms supporting hierarchical allocation, optimization, monitoring and control, and supporting resilient, energy efficient large-scale computing.

Abstract: Codeletset methods and/or apparatus may be used to enable resource-efficient computing. Such methods may involve decomposing a program into sets of codelets that may be allocated among multiple computing elements, which may enable parallelism and efficient use of the multiple computing elements. Allocation may be based, for example, on efficiencies with respect to data dependencies and/or communications among codelets.

Abstract: The present invention, known as runspace, relates to the field of computing system management, data processing and data communications, and specifically to synergistic methods and systems which provide resource-efficient computation, especially for decomposable many-component tasks executable on multiple processing elements, by using a metric space representation of code and data locality to direct allocation and migration of code and data, by performing analysis to mark code areas that provide opportunities for runtime improvement, and by providing a low-power, local, secure memory management system suitable for distributed invocation of compact sections of code accessing local memory. Runspace provides mechanisms supporting hierarchical allocation, optimization, monitoring and control, and supporting resilient, energy efficient large-scale computing.