As HPC shifts its long range focus from peta- to exascale, the need for programmers to be able to efficiently utilize the entirety of a machine’s compute resources has become more paramount. This has grown increasingly difficult as most of the Top500 machines utilize, in some capacity, hardware accelerators like GPUs and coprocessors which often require special languages and APIs to take advantage of them. In C++ the concept of executors, as currently discussed by the C++ standardization committee, has created a possibility for a flexible, and dynamic choice of the execution platform for various types of parallelism in C++, including the execution of user code on heterogeneous resources like accelerators and GPUs in a portable way. This will also allow to develop a solution that seamlessly integrates iterative execution (parallel algorithms) with other types of parallelism, such as task-based parallelism, asynchronous execution flows, continuation style computation, and explicit fork-join control flow of independent and non-homogeneous code paths.
HPX
HPX V0.9.11 Available!
The STE||AR Group is proud to announce the release of HPX v0.9.11! In this release our team has focused on developing higher level C++ programming interfaces which simplify the use of HPX in applications and ensure their portability in terms of code and performance. We paid particular attention to align all of these changes with the existing C++ Standards or with the ongoing standardization work. Other major features include the introduction of executors and various policies which enable to customize the ‘where’ and ‘when’ of task and data placement.
GSoC 2015 Results: Success!
This summer has been an exciting time for the STE||AR Group’s GSoC mentors and students alike! We were very pleased with the dedication and effort of all five of our participants. Our students made contributions to three of our software products: HPX, a distributed C++ runtime system which comes with a standards compliant API and allows users to scale their applications across thousands of machines; LibGeoDecomp, an auto-parallizing library for petascale computer simulations which is able to take advantage of HPX to better adapt fluctuating workloads to the system; and LibFlatArray, a highly efficient multidimensional array library which provides an object-oriented interface but stores data in a vectorization-friendly Struct-of-Arrays format.
CppCon 2015
Grant Mercer and I had the opportunity to present our talk, ‘Parallelizing the STL’, at Cppcon 2015. We both consider ourselves lucky for being able to attend the conference. The buzz of the atmosphere and C++ community was truly exciting to witness. Attendees were both from all over the world and performance critical industries such as 슬롯사이트 and other finance giants, as well scientific computing fields. As Jon Kalb highlighted in his talk, C++ is receiving a resurgence for several performance related reasons: Moore’s Law is coming to end and the subsequent shift to multi-core architectures, increased computational demands from the private sector, and the rise of power constrained mobile architectures. Combined with the interest in the standardization process, C++17 and beyond, there was a palpable excitement.
HPX Tutorial Promo Video
As a build up for our Supercomputing tutorial, the STE||AR Group has put together a promotional video to generate interest in HPX. The video gives viewer a high level overview of what HPX is and what will be discussed at the tutorial. The SC15 Tutorials Committee will circulate this and other tutorial videos on its YouTube playlist. We would like to thank our colleague Randy Dannenberg and his students for helping us put this together!
On Tour: HPX Tutorial at SC15!
Howdy! The STE||AR Group welcomes you to participate in a hands on HPX tutorial which will be given this year in Austin, Texas as part of the SC Tutorials program. STE||AR Fellows from Louisiana State University, Friedrich-Alexander Universitat, Lawrence Berkeley National Laboratory, and University of Oregon will present “Massively Parallel Task-Based Programming wih HPX” which will consist of five parts:
HPX and C++ Futures
There has been a lot of attention to Futures in C++ lately. One of the main related events (even if it was not widely mentioned anywhere) was the final call for positions and comments for the preliminary draft technical specification for C++ Extensions for Concurrency (PDTS), see N4538. This call closed on July 7th, 2015. At this point, the document is out for the national bodies to vote on whether it should be accepted as a final TS (the balloting period ends on July 22nd, 2015). Personally, I expect for this document to be accepted unanimously, which means that we soon will have a second TS related to parallelism and concurrency ready. Compiler vendors will have a field day implementing all of this functionality over the next months (and years).
HPX and PVS-Studio
We have used a trial version of PVS-Studio for HPX previously, but I vaguely remembered it as being very verbose in its diagnostics. I have read a lot about the tool lately, and since it was a long time since we used it, we contacted the developers at Viva64 asking whether they would be willing to support our open source project. We were positively surprised that they agreed to provide us with a free license for one year in exchange for a blog post about our experience with the tool.
HPX and C++ Distributed Computing
For us, HPX is a ‘A general purpose C++ runtime system for parallel and distributed applications of any scale’. While this is quite a mouthful, we mean every word of it. All of the recently published posts on this site so far have focused on the APIs HPX exposes for purely local operation on a single machine. In this installment I would like to start talking about how HPX exposes distributed functionality, i.e. how to use HPX to write truly distributed applications. As we will see, by introducing just minor extensions to the C++ standard the user is able to write homogeneous code without having to pay attention to any differences between invoking functionality locally (on the current node) or remotely (on any other node in a cluster).
HPX and C++ Parallel Algorithms
In Lenexa (May 2015), the C++ standardization committee has finalized the work related to the Technical Specification for C++ Extensions for Parallelism (the latest document at the time of this writing is N4507) . This document describes parallel algorithms which will extend and complement the (sequential) standard library algorithms we all love and use for over a decade now. This is an important – albeit only first – step towards standardizing higher level abstractions for parallelism and concurrency in C++.