Abstract—Current analytic solutions to the execution time distribution of a parallel composition of tasks having stochastic execution times are computationally complex, except for a limited number of distributions. In this paper, we present an analytical solution based on approximating execution time distributions in terms of the first four statistical moments. This low-cost approach allows the parallel execution time distribution to be approximated at ultra-low solution complexity for a wide range of execution time distributions. The accuracy of our method is experimentally evaluated for synthetic distributions as well as for task execution time distributions found i
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...
Classical analysis of real-time systems focuses on guaranteeing the schedulability of the system whe...
Systems controlled by embedded computers become indispensable in our lives and can be found in avion...
Performance modeling plays a significant role in predicting the effects of a particular design choic...
We obtain stochastic bounds on execution times of parallel computations assuming ideal conditions fo...
Predicting the execution time of parallel programs involves computing the maximum or minimum of the ...
Scheduling appears frequently in distributed, cloud and high-performance computing, as well as in em...
There is a current need for scheduling policies that can leverage the performance variability of res...
1 Introduction Parallel processing has emerged as an important means of achieving high computational...
This paper presents an approach to the analysis of task sets implemented on multiprocessor systems, ...
A number of identical machines operating in parallel are to be used to complete the processing of a ...
Characterizing the I/O requirements of parallel applications that manipulate huge amounts of data, s...
The problem of statically estimating the execution time distribution for a task graph consisting of ...
The uncertainty of running time of randomized algorithms provides a better opportunity for asynchron...
A main question in parallel computing is the following: Under which conditions should parallel task-...
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...
Classical analysis of real-time systems focuses on guaranteeing the schedulability of the system whe...
Systems controlled by embedded computers become indispensable in our lives and can be found in avion...
Performance modeling plays a significant role in predicting the effects of a particular design choic...
We obtain stochastic bounds on execution times of parallel computations assuming ideal conditions fo...
Predicting the execution time of parallel programs involves computing the maximum or minimum of the ...
Scheduling appears frequently in distributed, cloud and high-performance computing, as well as in em...
There is a current need for scheduling policies that can leverage the performance variability of res...
1 Introduction Parallel processing has emerged as an important means of achieving high computational...
This paper presents an approach to the analysis of task sets implemented on multiprocessor systems, ...
A number of identical machines operating in parallel are to be used to complete the processing of a ...
Characterizing the I/O requirements of parallel applications that manipulate huge amounts of data, s...
The problem of statically estimating the execution time distribution for a task graph consisting of ...
The uncertainty of running time of randomized algorithms provides a better opportunity for asynchron...
A main question in parallel computing is the following: Under which conditions should parallel task-...
A compile-time prediction technique is outlined that yields approximate, yet low-cost, analytical pe...
Classical analysis of real-time systems focuses on guaranteeing the schedulability of the system whe...
Systems controlled by embedded computers become indispensable in our lives and can be found in avion...