Hal Finkel via llvm-dev
2016-Dec-22 00:42 UTC
[llvm-dev] Postdoc Positions - LLVM for High-Performance Computing
Hi everyone,
I'm happy to report that I have two open postdoctoral research positions
at Argonne National Laboratory focusing on LLVM-based compiler
technology for high-performance computing. US citizenship is *not*
required. If you've received your Ph.D. within the past several years,
or are in the process of completing your degree requirements, and would
like to join a team working to prepare LLVM for the exascale era, I hope
you'll apply to one or both of these positions:
401877: http://bit.ly/2i7mVLl - 401878: http://bit.ly/2hShmQz
We'll be working with teams from several other laboratories and
universities, as well as the wider LLVM community, on topics ranging
from GPU register allocation to high-level optimizations of loops and
parallelism constructs. If you have any questions, please send me an
e-mail (hfinkel at anl.gov).
** Requisition 401877 - Optimization and Autotuning for Supercomputing
Compilers **
http://bit.ly/2i7mVLl
Position Description
This is an exciting opportunity to work on the future of compiler
technology for high-performance computing (HPC) with a particular focus
on supporting the world's largest supercomputers as we head toward
exascale. Theextremelevels of parallelism available on these machines
combined with their complex memory hierarchiescreateuniqueoptimization
challenges. This research will exploreenhancementsto LLVM enabling
better modeling and exploration of the complex space of potential
optimizations in addition toenhancingLLVM's optimization capabilities.
One focus of this work will be to enable more-effective autotuning by
strengthening the two-way communication between the autotuner and the
optimizer.
A passion forimprovingcompiler technology, a keen interest in
high-performance computing hardware, anda desireto advance scientific
computing, will be rewarded in this position.
Position Requirements
We expect you to have:
* Minimum education and experience or equivalent combination:
* Doctorate + 0 years.
* Experience with compiler and toolchain development, including
intermediate representations, machine-independent and
machine-dependent optimizations, and code generation; experience
with LLVM and Clang is preferred.
* Significant experience with C++, includingthe use oftemplates.
* Demonstrated knowledge of instruction sets and computer
architectures, including pipeline structure and hazards, and cache
and memory hierarchies.
* Experience with assembly languages, preferably at least one of
x86_64, PowerPC, and PTX.
* Demonstratedadvanced knowledge ofhigh-level compiler optimizations;
experience with polyhedral loop optimizations is preferred.
* Advanced knowledge ofthe language semantics of one of the following:
C, C++, Fortran.
* Advanced knowledge ofmathematical-optimization techniques,
especially derivative-free optimization.
* Experience with machine learning, especially supervised learning.
* Experience with high-performance computing and scientific code
development.
* Experience with code optimization andthe use ofprofiling and
performance-monitoring tools and techniques.
* Experience with Linux environments and Python.Good software
debugging skills.
In addition,candidatesshould show:
* Effective analytical andproblem-solvingskills
tocontributetocreativesolutions to complex problems.
* Good communications skills, both verbal and written.
* Goodcollaborativeskills, including the ability to work wellwith
otherlabs, universities, computing centers, and industry.
** Requisition 401878 - Parallelism, Memory, and Programming Models for
Supercomputing Compilers **
http://bit.ly/2hShmQz
Position Description
This is an exciting opportunity to work on the future of compiler
technology for high-performance computing (HPC) with a particular focus
on supporting the world's largest supercomputers as we head toward
exascale. Theextremelevels of parallelism available on these machines
combined with their complex memory
hierarchiescreateuniqueprogramming-model and optimization challenges.
This research will exploreenhancementsto LLVM enabling the explicit
representation and optimization of parallelism and hierarchical-memory
constructs.Enhancementsto programming models, including OpenMP, will be
prototyped as we learn how to best provide performance portability
across a range of future computing architectures.
A passion forimprovingcompiler technology, a keen interest in
high-performance computing hardware, anda desireto advance scientific
computing, will be rewarded in this position.
Position Requirements
We expect you to have:
* Experience with compiler and toolchain development, including
intermediate representations, machine-independent and
machine-dependent optimizations, and code generation; experience
with LLVM and Clang is preferred.
* Significant experience with C++, includingthe use oftemplates.
* Demonstrated knowledge of instruction sets and computer
architectures, including pipeline structure and hazards, and cache
and memory hierarchies.
* Experience with assembly languages, preferably at least one of
x86_64, PowerPC, and PTX.
* Demonstratedadvanced knowledge ofhigh-level compiler optimizations;
experience with polyhedral loop optimizations is preferred.
* Advanced knowledge ofthe language semantics of one of the following:
C, C++, Fortran.
* Experience with the OpenMP programming model.
* Experience with high-performance computing and scientific code
development.
* Experience with code optimization andthe use ofprofiling and
performance-monitoring tools and techniques.
* Experience with Linux environments and Python.
* Good software debugging skills.
In addition,candidatesshould show:
* Effective analytical andproblem-solvingskills
tocontributetocreativesolutions to complex problems.
* Good communications skills, both verbal and written.
* Goodcollaborativeskills, including the ability to work wellwith
otherlabs, universities, computing centers, and industry.
-Hal
--
Hal Finkel
Lead, Compiler Technology and Programming Languages
Leadership Computing Facility
Argonne National Laboratory
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