Above are papers related to the following paper: [Paper_ID] Paper #1134031. 	[Title] Modeling Superscalar Processors via Statistical Simulation [Abstract]  Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #709113. 	[Title] Theoretical Modeling of Superscalar Processor Performance [Abstract] The current trace-driven simulation approach to determine superscalar processor performance is widely used but has some shortcomings. Modern benchmarks generate extremely long traces, resulting in problems with data storage, as well as very long simulation run times. More fundamentally, simulation generally does not provide significant insight into the factors that determine performance or a characterization of their interactions. This paper proposes a theoretical model of superscalar processor performance that addresses these shortcomings. Performance is viewed as an interaction of program parallelism and machine parallelism. Both program and machine parallelisms are decomposed into multiple component functions. Methods for measuring or computing these functions are described. The functions are combined to provide a model of the interaction between program and machine parallelisms and an accurate estimate of the performance. The computed performance, based on this model, is compared to simulated performance for six benchmarks from the SPEC 92 suite on several configurations of the IBM RS/6000 instruction set architecture. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #8594. 	[Title] The Limits of Instruction Level Parallelism in SPEC95 Applications [Abstract] This paper examines the limits to instruction level parallelism that can be found in programs, in particular the SPEC95 benchmark suite. It differs from earlier studies in removing non-essential true dependencies that occur as a result of the compiler employing a stack for subroutine linkage. This is a subtle limitation to parallelism that is not readily evident as it appears as a true dependency on the stack pointer. In this paper we show that its removal exposes far more parallelism than has been seen previously. We refer to this type of parallelism as "parallelism at a distance" because it requires impossibly large instruction windows for detection. We conclude with two observations: 1) that a single instruction window characteristic of superscalar machines is inadequate for detecting parallelism at a distance; and 2) in order to take advantage of this parallelism the compiler must be involved, or separate threads must be explicitly programmed. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #8591. 	[Title] Limits of Control Flow on Parallelism [Abstract] This paper discusses three techniques useful in relaxing the constraints imposed by control flow on parallelism: control dependence analysis, executing multiple flows of control simultaneously, and speculative execution. We evaluate these techniques by using trace simulations to find the limits of parallelism for machines that employ different combinations of these techniques. We have three major results. First, local regions of code have limited parallelism, and control dependence analysis is useful in extracting global parallelism from different parts of a program. Second, a superscalar processor is fundamentally limited because it cannot execute independent regions of code concurrently. Higher performance can be obtained with machines, such as multiprocessors and dataflow machines, that can simultaneously follow multiple flows of control. Finally, without speculative execution to allow instructions to execute before their control dependences are resolved, only modest amounts of parallelism can be obtained for programs with complex control flow. Please summarise all the given information.

Paper #1134031 has the title `Modeling Superscalar Processors via Statistical Simulation  
` and the abstract `nan`.
Question: Which category should Paper #1134031 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #1134031 has the title `Modeling Superscalar Processors via Statistical Simulation  
` and the abstract `nan`.
Question: Which category should Paper #1134031 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Rule_Learning