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Dr. Philip Cannata 1 Hmm Projects C Structs or Classes or OO in Hmm10 Continuations in Hmm6 Trees, Binary Trees or Linked lists in Hmm3 Prolog in Hmm2.

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Presentation on theme: "Dr. Philip Cannata 1 Hmm Projects C Structs or Classes or OO in Hmm10 Continuations in Hmm6 Trees, Binary Trees or Linked lists in Hmm3 Prolog in Hmm2."— Presentation transcript:

1 Dr. Philip Cannata 1 Hmm Projects C Structs or Classes or OO in Hmm10 Continuations in Hmm6 Trees, Binary Trees or Linked lists in Hmm3 Prolog in Hmm2 Dictionaries or Hashmaps in Hmm2 Matricies in Hmm2 Type inferencing in Hmm1 Code Annotation of Hmm1 Cons, cdr, car, rand, math in Hmm1 Explicit Polymorphism in Hmm1 letrec in Hmm2 Thread Blocks in Hmm1 Memoization in Hmm1 Hmm + Python1 Map, Reduce and Filter in Hmm1 Objective Hmm1 SQL in Hmm13780% Non-Hmm Projects Lisp3 Uro Lite - Data Block and Exec Block1 Polite1 lambda Calculus in Haskell1 Flash Cards1 Haskell from scratch1 Monotony Web Development1920% 46

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4 Dr. Philip Cannata 4 Sample Project Presentations Hmm + Continuations - Timothy Joslin and Stephen Kimberlin Hmm + Structs - Chris Cunningham and Alex Espinosa Parallel Hmm - Garrett Lancaster and Phillip Birtcher

5 Dr. Philip Cannata 5 Parallel Computing Abstract: In December 2006 we published a broad survey of the issues for the whole field concerning the multicore/manycore sea change (see view.eecs.berkeley.edu). We view the ultimate goal as being able to productively create efficient, correct and portable software that smoothly scales when the number of cores per chip doubles biennially. This talk covers the specific research agenda that a large group of us at Berkeley are going to follow (see parlab.eecs.berkeley.edu) as part of a center funded for five years by Intel and Microsoft. To take a fresh approach to the longstanding parallel computing problem, our research agenda will be driven by compelling applications developed by domain experts in personal health, image retrieval, music, speech understanding and browsers. The development of parallel software is divided into two layers: an efficiency layer that aims at low overhead for 10 percent of the best programmers, and a productivity layer for the rest of the programming community-including domain experts-that reuses the parallel software developed at the efficiency layer. Key to this approach is a layer of libraries and programming frameworks centered around the 13 design patterns that we identified in the Berkeley View report. We rely on autotuning to map the software efficiently to a particular parallel computer. The role of the operating systems and the architecture in this project is to support software and applications in achieving the ultimate goal. Examples include primitives like thin hypervisors and libraries for the operating system and hardware support for partitioning and fast barrier synchronization. We will prototype the hardware of the future using field programmable gate arrays (FPGAs) on a common hardware platform being developed by a consortium of universities and companies (see http://ramp.eecs.berkeley.edu/ ).http://ramp.eecs.berkeley.edu/

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