- Conference Chairs:
- Hal Finkel,
- Jeff Hammond
- Sponsor:
- sighpc
LLVM, winner of the 2012 ACM Software System Award, has become an integral part of the software-development ecosystem for optimizing compilers, dynamic-language execution engines, source-code analysis and transformation tools, debuggers and linkers, and a whole host of programming-language and toolchain-related components. Now heavily used in both academia and industry, where it allows for rapid development of production-quality tools, LLVM is increasingly used in work targeted at high-performance computing. Research in and implementation of programming-language analysis, compilation, execution and profiling has clearly benefited from the availability of a high-quality, freely-available infrastructure on which to build.
LLVM-HPC'14 is the first workshop specifically focusing on research making use of the LLVM compiler infrastructure in High-Performance Computing (HPC). The call for papers attracted six submissions, and after peer review by the program committee, five of these were accepted. The accepted papers cover a wide variety of topics: enabling high-performance standards-driven development, code profiling and optimization, and tools that greatly enhance programmer productivity. We expect that all of these topics will be of considerable interest to the wider HPC community.
Proceeding Downloads
PACXX: Towards a Unified Programming Model for Programming Accelerators Using C++14
We present PACXX -- a unified programming model for programming many-core systems that comprise accelerators like Graphics Processing Units (GPUs). One of the main difficulties of the current GPU programming is that two distinct programming models are ...
Coordinating GPU threads for OpenMP 4.0 in LLVM
- Carlo Bertolli,
- Samuel F. Antao,
- Alexandre E. Eichenberger,
- Kevin O'Brien,
- Zehra Sura,
- Arpith C. Jacob,
- Tong Chen,
- Olivier Sallenave
GPUs devices are becoming critical building blocks of High-Performance platforms for performance and energy efficiency reasons. As a consequence, parallel programming environment such as OpenMP were extended to support offloading code to such devices. ...
SamplePGO: the power of profile guided optimizations without the usability burden
Profile-guided optimizations (PGO) offer more optimization opportunities that are typically hard to obtain with static heuristics and techniques. In several application domains, significant performance can be gained by using runtime profiles to guide ...
Architecture-independent modeling of intra-node data movement
A primary concern of future high performance systems is the way data movement is managed; the sheer scale of data to be processed directly affects the achievable performance these systems can attain. However, the increasingly complex but inherently ...
Towards providing low-overhead data race detection for large OpenMP applications
- Joachim Protze,
- Simone Atzeni,
- Dong H. Ahn,
- Martin Schulz,
- Ganesh Gopalakrishnan,
- Matthias S. Müller,
- Ignacio Laguna,
- Zvonimir Rakamarić,
- Greg L. Lee
Neither static nor dynamic data race detection methods, by themselves, have proven to be sufficient for large HPC applications, as they often result in high runtime overheads and/or low race-checking accuracy. While combined static and dynamic ...
- Proceedings of the 2014 LLVM Compiler Infrastructure in HPC
Recommendations
Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| LLVM-HPC'17 | 10 | 9 | 90% |
| LLVM '15 | 12 | 7 | 58% |
| Overall | 22 | 16 | 73% |