*第13回AT研究会オープンアカデミックセッション(ATOS13) [#f43bff49]

 日時:2015年12月11日(金) 13:15~15:00 (13:00より開場)

(会場建物情報) http://www.u-tokyo.ac.jp/campusmap/cam01_13_01_j.html~

**講演1. 13:15~14:00 The Xevolver Project: Separation of Concerns for Supporting Legacy Code Migration [#p3cdd7d3]

***講演者: Hiroyuki Takizawa (Tohoku University) [#ba3a5d31]

***概要: [#u58f4ca5]

We are developing a code transformation framework, Xevolver, to allow
users to define their own code transformation rules and also to
customize typical rules for individual applications and systems.  By
expressing system-awareness as code transformations, users do not need
to directly modify the application code for system-aware performance
optimizations. This prevents the application code from being
specialized for a particular HPC system, and thereby the application
can be expected to achieve high performance portability across system
generations. The Xevolver framework uses standard XML technologies to
represent code transformations at a low level.  In addition, some
high-level interfaces and tools for expressing user-defined code
transformation rules are now under active development. In this talk,
our research activities and some case studies are introduced to
discuss the strengths and limitations of our approach to separation of
system-awareness from application codes.

** 講演2. 14:00~15:00 The Role of Compiler Optimization and Autotuning for Reducing Data Movement in High-Performance Applications [#u0fc4437]

*** 講演者:Mary Hall (University of Utah) [#xb02dd30]

*** 概要: [#t695bab9]

As the cost of moving data on current and future architectures becomes
increasingly dominant, the challenges of developing high-performance
applications are increasingly onerous. The goal of compiler
optimization in high-performance computing is to take as input a
computation that is architecture independent and maintainable and
produce as output efficient implementations of the computation tuned
for the target architecture. Autotuning empirically evaluates a search
space of possible implementations of a computation to identify the
implementation that best meets its optimization criteria (e.g.,
performance, power, or both). Combining the two concepts, autotuning
compilers generate this search space of highly-tuned implementations
either automatically or with programmer guidance. This talk will
explore the role of compiler technology in achieving very high levels
of performance, comparable to what is obtained manually by experts. As
a case study, it will highlight some of the aggressive optimizations
required to reduce communication for a specific high-performance
application domain that is notoriously memory bound: geometric
multigrid and the stencil computations within them.

** 問合せ先 [#yc24225d]

東北大学 滝沢寛之~
E-mail: takizawa[at]cc.tohoku.ac.jp ([at]を@に置き換えてください)

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