Abstract:
A system for, method of and computer program product captures performance- characteristic data from the execution of a program and models system performance based on that data. Performance-characterization data based on easily captured reuse distance metrics is targeted, defined as the total number of memory references between two accesses to the same piece of data. Methods for efficiently capturing this kind of metrics are described. These data can be refined into easily interpreted performance metrics, such as performance data related to caches with LRU replacement and random replacement strategies in combination with fully associative as well as limited associativity cache organizations. Methods for assessing cache utilization as well as parallel execution are covered.
Abstract:
The disclosed embodiments relate to a system that provides an intelligent port infrastructure for communication network devices. This is accomplished by incorporating a highly configurable pre-classifier module into the port infrastructure. This pre-classifier makes it possible to realign packet data to add a configurable number of bytes to the front of the packet, and also to select interesting data from incoming packets for further analysis. The selected data is sent into a configurable classification engine, which generates instructions that specify how to determine associated packet attributes. The packet attributes are then generated based on the instructions, and are forwarded along with the packet to downstream processing units.
Abstract:
A system for, method of and computer program product captures performance- characteristic data from the execution of a program and models system performance based on that data. Performance-characterization data based on easily captured reuse distance metrics is targeted, defined as the total number of memory references between two accesses to the same piece of data. Methods for efficiently capturing this kind of metrics are described. These data can be refined into easily interpreted performance metrics, such as performance data related to caches with LRU replacement and random replacement strategies in combination with fully associative as well as limited associativity cache organizations. Methods for assessing cache utilization as well as parallel execution are covered.
Abstract:
A system for, method of and computer program product captures performance characteristic data from the execution of a program and models system performance based on that data. Performance-characterization data (140) based on easily captured reuse distance metric is targeted, defined as the total number of memory references (230) between two accesses to the same piece of data (240). Methods for efficiently capturing this kind of metrics are described. These data can be refined into easily interpreted performance metrics, such as performance data related to caches with LRU replacement and random replacement strategies in combination with fully associative as well as limited associativity cache organaziations (330). Methods for assesing cache utilization as well as parallel execution are covered.
Abstract:
A system for, method of and computer program product captures performance- characteristic data from the execution of a program and models system performance based on that data. Performance-characterization data based on easily captured reuse distance metrics is targeted, defined as the total number of memory references between two accesses to the same piece of data. Methods for efficiently capturing this kind of metrics are described. These data can be refined into easily interpreted performance metrics, such as performance data related to caches with LRU replacement and random replacement strategies in combination with fully associative as well as limited associativity cache organizations.
Abstract:
A system for, method of and computer program product captures performance-characteristic data from the execution of a program and models system performance based on that data. Performance-characterization data based on easily captured reuse distance metrics is targeted, defined as the total number of memory references between two accesses to the same piece of data. Methods for efficiently capturing this kind of metrics are described. These data can be refined into easily interpreted performance metrics, such as performance data related to caches with LRU replacement and random replacement strategies in combination with fully associative as well as limited associativity cache organizations. Methods for assessing cache utilization as well as parallel execution are covered.
Abstract:
A system for, method of and computer program product captures performance- characteristic data from the execution of a program and models system performance based on that data. Performance-characterization data based on easily captured reuse distance metrics is targeted, defined as the total number of memory references between two accesses to the same piece of data. Methods for efficiently capturing this kind of metrics are described. These data can be refined into easily interpreted performance metrics, such as performance data related to caches with LRU replacement and random replacement strategies in combination with fully associative as well as limited associativity cache organizations.