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  2. Worst-case execution time - Wikipedia

    en.wikipedia.org/wiki/Worst-case_execution_time

    These markers result in a trace of execution, which includes both the path taken through the program and the time at which different points were executed. The trace is then analyzed to determine the maximum time that each part of the program has ever taken to execute, what the maximum observed iteration time of each loop is and whether there ...

  3. Dynamic program analysis - Wikipedia

    en.wikipedia.org/wiki/Dynamic_program_analysis

    Dynamic symbolic execution (also known as DSE or concolic execution) involves executing a test program on a concrete input, collecting the path constraints associated with the execution, and using a constraint solver (generally, an SMT solver) to generate new inputs that would cause the program to take a different control-flow path, thus ...

  4. Speedup - Wikipedia

    en.wikipedia.org/wiki/Speedup

    T is the execution time of the task; W is the execution workload of the task. Throughput of an architecture is the execution rate of a task: = = =, where ρ is the execution density (e.g., the number of stages in an instruction pipeline for a pipelined architecture);

  5. Least slack time scheduling - Wikipedia

    en.wikipedia.org/wiki/Least_slack_time_scheduling

    Least slack time (LST) scheduling is an algorithm for dynamic priority scheduling. It assigns priorities to processes based on their slack time . Slack time is the amount of time left after a job if the job was started now.

  6. Earliest deadline first scheduling - Wikipedia

    en.wikipedia.org/wiki/Earliest_deadline_first...

    For example, when using Linux as host OS and KVM as hypervisor, IRMOS can be used to provide scheduling guarantees to individual VMs and at the same time isolate their performance so as to avoid undesired temporal interferences. IRMOS features a combined EDF/FP hierarchical scheduler. At the outer level there is a partitioned EDF scheduler on ...

  7. Analysis of parallel algorithms - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_parallel...

    Minimizing the depth/span is important in designing parallel algorithms, because the depth/span determines the shortest possible execution time. [8] Alternatively, the span can be defined as the time T ∞ spent computing using an idealized machine with an infinite number of processors. [9] The cost of the computation is the quantity pT p. This ...