[www] r261086 - [EuroLLVM] Add lightning talks abstracts.

Wed Feb 17 04:51:58 PST 2016

Author: aadg
Date: Wed Feb 17 06:51:58 2016
New Revision: 261086

URL: http://llvm.org/viewvc/llvm-project?rev=261086&view=rev
Log:
[EuroLLVM] Add lightning talks abstracts.

Modified:
    www/trunk/devmtg/2016-03/index.html

Modified: www/trunk/devmtg/2016-03/index.html
URL: http://llvm.org/viewvc/llvm-project/www/trunk/devmtg/2016-03/index.html?rev=261086&r1=261085&r2=261086&view=diff
==============================================================================

--- www/trunk/devmtg/2016-03/index.html (original)
+++ www/trunk/devmtg/2016-03/index.html Wed Feb 17 06:51:58 2016
@@ -277,6 +277,130 @@ audience, especially when considering we
 </p>
 
 <div class="www_sectiontitle" id="LightningTalksAbstracts">Lightning talks abstracts</div>
+<p>
+<b><a id="lightning1">Random Testing of the LLVM Code Generator</a></b><br>
+<i>Bevin Hansson - SICS Swedish ICT</i><br>
+LLVM is a large, complex piece of software with many interlocking components.
+Testing a system of this magnitude is an arduous task. Random testing is an
+increasingly popular technique used to test complex systems. A successful
+example of this is Csmith, a tool which generates random, semantically valid C
+programs.
+</p><p>
+We present a generic method to generate random but structured intermediate
+representation code. Our method is implemented in LLVM to generate random
+Machine IR code for testing the post-instruction selection stages of code
+generation.
+</p>
+
+<p>
+<b><a id="lightning2">ARCHER: Effectively Spotting Data Races in Large OpenMP Applications</a></b><br>
+<i>Simone Atzeni - University of Utah</i><br>
+<i>Ganesh Gopalakrishnan - University of Utah</i><br>
+<i>Zvonimir Rakamaric - University of Utah</i><br>
+<i>Dong H. Ahn - Lawrence Livermore National Laboratory</i><br>
+<i>Ignacio Laguna - Lawrence Livermore National Laboratory</i><br>
+<i>Martin Schulz - Lawrence Livermore National Laboratory</i><br>
+<i>Gregory L. Lee - Lawrence Livermore National Laboratory</i><br>
+Although the importance OpenMP as a parallel programming model and its adoption
+in Clang/LLVM is increasing (OpenMP 3.1 is now fully supported by Clang/LLVM
+3.7), existing data-race checkers for OpenMP have high overheads and generate
+many false positives. In this work, we propose the first OpenMP data race
+checker, ARCHER, that achieves high accuracy and low overheads on large OpenMP
+applications. Built on top of LLVM/Clang and the ThreadSanitizer (TSan) dynamic
+race checker, ARCHER incorporates scalable happens-before tracking, and
+exploits structured parallelism via combined static and dynamic analysis, and
+modularly interfaces with OpenMP runtimes. ARCHER significantly outperforms
+TSan and Intel Inspector XE, while providing the same or better precision. It
+has helped detect critical data races in the Hypre library that is central to
+many projects at the Lawrence Livermore National Laboratory (LLNL) and
+elsewhere.
+</p><p>
+Note: this lightning has an associated <a href="#poster1">poster</a>
+</p>
+
+<p>
+<b><a id="lightning3">Hierarchical Graph Coloring Register Allocation in LLVM</a></b><br>
+<i>Aaron Smith - Microsoft Research</i><br>
+This talk will present a new register allocator for LLVM based on a
+hierarchical graph coloring approach. In this allocator a program's control
+structure is represented as a tree of tiles and a two phase algorithm colors
+the tiles based on both local and global information. This talk will describe
+our implementation in LLVM along with an initial comparison to LLVM's existing
+greedy allocator.
+</p>
+
+<p>
+<b><a id="lightning4">Retargeting LLVM to an Explicit Data Graph Execution (EDGE) Architecture</a></b><br>
+<i>Aaron Smith - Microsoft Research</i><br>
+This talk will describe recent work to retarget LLVM to an Explicit Data Graph
+Execution (EDGE) architecture. EDGE architectures utilize a hybrid von
+Neumann/dataflow execution model which provides out of order execution with
+near in-order power efficiency. We will describe the challenges with targeting
+an EDGE ISA with LLVM and compare our LLVM based EDGE compiler with a mature
+production quality Visual Studio based EDGE toolchain.
+</p>
+
+<p>
+<b><a id="lightning5">Optimal Register Allocation and Instruction Scheduling for LLVM</a></b><br>
+<i>Roberto Castañeda Lozano - SICS & Royal Institute of Technology (KTH)</i><br>
+<i>Gabriel Hjort Blindell - Royal Institute of Technology (KTH)</i><br>
+<i>Mats Carlsson - SICS</i><br>
+<i>Christian Schulte - SICS & Royal Institute of Technology (KTH)</i><br>
+This talk presents Unison - a simple, flexible and potentially optimal tool
+that solves register allocation and instruction scheduling simultaneously.
+Experiments using MediaBench and Hexagon show that Unison can speed up the code
+code generated by LLVM by up to 30%.
+</p><p>
+Unison is fully integrated with LLVM's code generator and hence can be used as
+a complement to the existing heuristic algorithms. From a LLVM developer's
+perspective, the ability to deliver optimal code makes Unison a powerful tool
+to design and evaluate heuristics. From a user's perspective, Unison allows
+compilation time to be traded for code quality beyond the usual -O{0,1,2,3,..}
+optimization levels.
+</p>
+
+<p>
+<b><a id="lightning6">Towards fully open source GPU accelerated molecular dynamics simulation</a></b><br>
+<i>Vedran Miletić - Heidelberg Institute for Theoretical Studies</i><br>
+<i>Szilárd Páll - Royal Institute of Technology (KTH)</i><br>
+<i>Frauke Gräter - Heidelberg Institute for Theoretical Studies</i><br>
+Molecular dynamics is a simulation method for studying movements of atoms and
+molecules, usually applied in the study of biomolecules and materials. GROMACS
+open source molecular dynamics simulator supports GPU acceleration using both
+CUDA and OpenCL. While using CUDA is limited to NVIDIA GPUs and NVIDIA
+proprietary drivers, compilers and libraries, OpenCL in GROMACS targets both
+NVIDIA and AMD GPUs. Until this point, OpenCL in GROMACS was only tested on
+proprietary drivers from NVIDIA and AMD.
+</p><p>
+Advances in AMDGPU LLVM backend and radeonsi Gallium compute stack for Radeon
+Graphics Core Next (GCN) GPUs are steadily closing the feature gap between the
+open source and proprietary drivers. Recent announcement from AMD regarding the
+plan to support the existing open source OpenCL driver and open source their
+(currently proprietary) OpenCL driver makes it feasible to run GPU accelerated
+molecular dynamics on fully open source OpenCL stack.
+</p><p>
+Under the guidance and with help from AMD's developers working on LLVM, we are
+working on improving AMDGPU LLVM backend, radeonsi Gallium compute stack, and
+libclc to support the OpenCL features GROMACS requires to run. The lightning
+talk will present the challenges we encountered in the process.
+</p>
+
+<p>
+<b><a id="lightning7">CSiBE in the LLVM ecosystem</a></b><br>
+<i>Gabor Ballabas - Department of Software Engineering, University of Szeged</i><br>
+<i>Gabor Loki - Department of Software Engineering, University of Szeged</i><br>
+More than a decade ago, we have started to set up a code size benchmarking
+environment for compilers - called CSiBE - which became the official code size
+benchmark of GNU GCC. Since then, lots of open source and industrial compilers
+and testing frameworks have integrated it in their system for benchmarking and
+testing purpose. Nowadays CSiBE is getting increasing attention on the field of
+IoT again. Since the benchmark environment of CSiBE feels old and complex for
+the current modularized world, we have started to update its core. We are
+extending CSiBE with a user friendly interface, modularized testbeds, support
+for embedders and support for LLVM-based compilers (e.g., Clang and Rust). We
+will share our experiences and the possibilities about CSiBE for the community.
+</p>
+
 <div class="www_sectiontitle" id="PostersAbstracts">Posters abstracts</div>
 <p>
 <b><a id="poster1">ARCHER: Effectively Spotting Data Races in Large OpenMP Applications</a></b><br>
@@ -300,6 +424,8 @@ TSan and Intel Inspector XE, while provi
 has helped detect critical data races in the Hypre library that is central to
 many projects at the Lawrence Livermore National Laboratory (LLNL) and
 elsewhere.
+</p><p>
+Note: this poster has an associated <a href="#lightning2">lightning talk</a>
 </p>
 
 <p>


