How to Communicate Poorly: giving bad talks, show bad posters, writing bad papers7 Talk Commandments for a Bad CareerFollowing all the commandments in Powerpoint!7 Poster Commandments for a Bad CareerFollowing all the commandments5 Writing Commandments for a Bad CareerAlternatives to Bad TalksAlternatives to Bad Posters (from Randy Katz)PowerPoint PresentationAlternatives to Bad PapersAdministriviaDAP Spr.‘01 ©UCB 1 How to Communicate Poorly: How to Communicate Poorly: giving bad talks, show bad posters, giving bad talks, show bad posters, writing bad papers writing bad papers Professor David A. PattersonDecember 2004www.cs.berkeley.edu/~pattrsn/talks/nontech.htmlDAP Feb.‘04 ©UCB 27 Talk Commandments for a Bad CareerI. Thou shalt not illustrate.II. Thou shalt not covet brevity.III. Thou shalt not print large.IV.Thou shalt not use color.V. Thou shalt cover thy naked slides.VI. Thou shalt not skip slides in a long talk.VII. Thou shalt not practice.DAP Feb.‘04 ©UCB 3Following all the commandments in Powerpoint!•We describe the philosophy and design of the control flow machine, and present the results of detailed simulations of the performance of a single processing element. Each factor is compared with the measured performance of an advanced von Neumann computer running equivalent code. It is shown that the control flow processor compares favorably in the program.•We present a denotational semantics for a logic program to construct a control flow for the logic program. The control flow is defined as an algebraic manipulator of idempotent substitutions and it virtually reflects the resolution deductions. We also present a bottom-up compilation of medium grain clusters from a fine grain control flow graph. We compare the basic block and the dependence sets algorithms that partition control flow graphs into clusters. •A hierarchical macro-control-flow computation allows them to exploit the coarse grain parallelism inside a macrotask, such as a subroutine or a loop, hierarchically. We use a hierarchical definition of macrotasks, a parallelism extraction scheme among macrotasks defined inside an upper layer macrotask, and a scheduling scheme which assigns hierarchical macrotasks on hierarchical clusters.•We apply a parallel simulation scheme to a real problem: the simulation of a control flow architecture, and we compare the performance of this simulator with that of a sequential one. Moreover, we investigate the effect of modeling the application on the performance of the simulator. Our study indicates that parallel simulation can reduce the execution time significantly if appropriate modeling is used.•We have demonstrated that to achieve the best execution time for a control flow program, the number of nodes within the system and the type of mapping scheme used are particularly important. In addition, we observe that a large number of subsystem nodes allows more actors to be fired concurrently, but the communication overhead in passing control tokens to their destination nodes causes the overall execution time to increase substantially.•The relationship between the mapping scheme employed and locality effect in a program are discussed. The mapping scheme employed has to exhibit a strong locality effect in order to allow efficient execution•Medium grain execution can benefit from a higher output bandwidth of a processor and finally, a simple superscalar processor with an issue rate of ten is sufficient to exploit the internal parallelism of a cluster. Although the technique does not exhaustively detect all possible errors, it detects nontrivial errors with a worst-case complexity quadratic to the system size. It can be automated and applied to systems with arbitrary loops and nondeterminism.DAP Feb.‘04 ©UCB 47 Poster Commandments for a Bad CareerI. Thou shalt not illustrate.II. Thou shalt not covet brevity.III. Thou shalt not print large.IV.Thou shalt not use color.V. Thou shalt not attract attention to thyself.VI. Thou shalt not prepare a short oral overview. VII. Thou shalt not prepare in advance.DAP Feb.‘04 ©UCB 5Following all the commandmentsWe describe the philosophy and design of the control flow machine, and present the results of detailed simulations of the performance of a single processing element. Each factor is compared with the measured performance of an advanced von Neumann computer running equivalent code. It is shown that the control flow processor compares favorably in the program.We present a denotational semantics for a logic program to construct a control flow for the logic program. The control flow is defined as an algebraic manipulator of idempotent substitutions and it virtually reflects the resolution deductions. We also present a bottom-up compilation of medium grain clusters from a fine grain control flow graph. We compare the basic block and the dependence sets algorithms that partition control flow graphs into clusters. Our compiling strategy is to exploit coarse-grain parallelism at function application level: and the function application level parallelism is implemented by fork-join mechanism. The compiler translates source programs into control flow graphs based on analyzing flow of control, and then serializes instructions within graphs according to flow arcs such that function applications, which have no control dependency, are executed in parallel.A hierarchical macro-control-flow computation allows them to exploit the coarse grain parallelism inside a macrotask, such as a subroutine or a loop, hierarchically. We use a hierarchical definition of macrotasks, a parallelism extraction scheme among macrotasks defined inside an upper layer macrotask, and a scheduling scheme which assigns hierarchical macrotasks on hierarchical clusters.We apply a parallel simulation scheme to a real problem: the simulation of a control flow architecture, and we compare the performance of this simulator with that of a sequential one. Moreover, we investigate the effect of modeling the application on the performance of the simulator. Our study indicates that parallel simulation can reduce the execution time significantly if appropriate modeling is used.We have demonstrated that to achieve the best execution time for a control flow program, the number of nodes within the system and the type of mapping scheme used are particularly important. In addition, we observe that a large number of subsystem nodes allows more
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