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Weblog Articles Tagged with '#stxxl'

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Photo of a Samsung NVMe SSD

NVMe "Disk" Bandwidth and Latency for Batched Block Requests

Posted on 2019-03-22 16:00 by Timo Bingmann at Permlink with 0 Comments. Tags: #c++ #stxxl #thrill

Last week I had the pleasure of being invited to the Dagstuhl seminar 19111 on Theoretical Models of Storage Systems. I gave a talk on the history of STXXL and Thrill, but also wanted to include some current developments. Most interesting I found is the gap closing between RAM and disk bandwidth due to the (relatively) new Non-Volatile Memory Express (NVMe) storage devices.

Since I am involved in many projects using external memory, I decided to perform a simple set of fundamental experiments to compare rotational disks and newer solid-state devices (SSDs). The results were interesting enough to write this blog article about.

Among the tools of STXXL/FOXXLL there are two benchmarks which perform two distinct access patterns: Scan (benchmark_disks) and Random (benchmark_disks_random).

  • In Scan a batch of k sequential blocks of size B are read or written in order.
    Batched Scanning Pattern
  • In Random a batch of k randomly selected blocks of size B from a span of size N are read or written.
    Batched Random Access Pattern

The Scan experiment is probably the fastest access method as it reads or writes the disk (actually: storage device) sequentially. The Random experiment is good to determine the access latency of the disk as it first has to seek to the block and then transfer the data. Notice that the Random experiment does batched block accesses like one would perform in a query/answering system where the next set of random blocks depends on calculations performed with the preceding blocks (like in a B-Tree). This is a different experiment than done by most "throughput" measurement tools which issue a continuous stream of random block accesses.

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First slide of the talk

Presentation "STXXL and Thrill (Parallel Batch Processing)" at STXXL Workshop in DFG SPP 1736

Posted on 2016-09-21 20:00 by Timo Bingmann at Permlink with 0 Comments. Tags: #talk #thrill #stxxl

Today, I gave a technical presentation comparing STXXL and Project Thrill at the STXXL Workshop organized within the DFG SPP 1736. The main topic of the workshop was to determine the future development course of STXXL, and the biggest question in this regard was how to bring more multi-core parallelization into STXXL. Thrill or an adaptation of its ideas may be the solution to this challenge: 2016-09-21 STXXL and Thrill Slides.pdf 2016-09-21 STXXL and Thrill Slides.pdf.

Download 2016-09-21 STXXL and Thrill Slides.pdf

First slide of the talk showing priority queues at the airport

Presentation of Parallel Priority Queue at the Conference SEA'2015

Posted on 2015-06-30 17:11 by Timo Bingmann at Permlink with 0 Comments. Tags: #c++ #talk #stxxl

We are very glad to have been given the opportunity to present our work on bulk-parallel priority queues for external memory at the 14th International Symposium on Experimental Algorithms (SEA 2015) in Paris. Our paper is in the proceedings and also available here: paper-SEA15-Bulk-Parallel-Priority-Queue.pdf paper-SEA15-Bulk-Parallel-Priority-Queue.pdf

The talk was given by Thomas Keh, and the slides of the presentation are available online: 2015-06-29 A Bulk-Parallel Priority Queue in External Memory with STXXL.pdf 2015-06-29 A Bulk-Parallel Priority Queue in External Memory with STXXL.pdf. The implementation is available in the current master branch of STXXL at github.

Download 2015-06-29 A Bulk-Parallel Priority Queue in External Memory with STXXL.pdf

Abstract

We propose the design and an implementation of a bulk-parallel external memory priority queue to take advantage of both shared-memory parallelism and high external memory transfer speeds to parallel disks. To achieve higher performance by decoupling item insertions and extractions, we offer two parallelization interfaces: one using "bulk" sequences, the other by defining "limit" items. In the design, we discuss how to parallelize insertions using multiple heaps, and how to calculate a dynamic prediction sequence to prefetch blocks and apply parallel multiway merge for extraction. Our experimental results show that in the selected benchmarks the priority queue reaches 64% of the full parallel I/O bandwidth of SSDs and 49% of rotational disks, or the speed of sorting in external memory when bounded by computation.


Two figures from the technical report

A Bulk-Parallel Priority Queue in External Memory with STXXL

Posted on 2015-04-03 14:54 by Timo Bingmann at Permlink with 0 Comments. Tags: #research #stxxl

Today, our technical report on "A Bulk-Parallel Priority Queue in External Memory with STXXL" is now available on arXiv as 1504.00545 or locally: 1504.00545v1.pdf 1504.00545v1.pdf with source 1504.00545v1.tar.gz 1504.00545v1.tar.gz (130 KiB). A big thanks goes to Thomas Keh for the hard work he did in his bachelor thesis, and to Peter Sanders for all the insights into priority queues. The technical report is an extended version of our paper that will appear at the 14th International Symposium on Experimental Algorithms - SEA 2015.

Download 1504.00545v1.pdf

The bulk-parallel priority queue is current available in the development repository of STXXL on Github.

On 2015-06-29, Thomas Keh presented the PPQ at SEA'15 in Paris.

Abstract

We propose the design and an implementation of a bulk-parallel external memory priority queue to take advantage of both shared-memory parallelism and high external memory transfer speeds to parallel disks. To achieve higher performance by decoupling item insertions and extractions, we offer two parallelization interfaces: one using "bulk" sequences, the other by defining "limit" items. In the design, we discuss how to parallelize insertions using multiple heaps, and how to calculate a dynamic prediction sequence to prefetch blocks and apply parallel multiway merge for extraction. Our experimental results show that in the selected benchmarks the priority queue reaches 75% of the full parallel I/O bandwidth of rotational disks and and 65% of SSDs, or the speed of sorting in external memory when bounded by computation.

STXXL simple logo

Released STXXL 1.4.1

Posted on 2014-10-29 11:17 by Timo Bingmann at Permlink with 0 Comments. Tags: #c++ #university #stxxl

STXXL is an implementation of the C++ standard template library STL for external memory (out-of-core) computations, i.e., STXXL implements containers and algorithms that can process huge volumes of data that only fit on disks. While the compatibility to the STL supports ease of use and compatibility with existing applications, another design priority is high performance.

More history about STXXL can be found in the blog post to 1.4.0. Today, the second release of the new 1.4 branch was published:

What's new in 1.4.1 ?

  • Integrated support for kernel based asynchronous I/O on Linux (new file type "linuxaio"), which exploits Native Command Queuing (NCQ) if available.
  • Merged stxxl::unordered_map branch, which provides a hash map backed by external memory.
  • Replaced struct default_completion_handler with a NULL pointer, thus avoiding superfluous new/delete work for each I/O request.
  • Added stxxl::external_shared_ptr which is a proxy class to allow use of shared_ptr classes inside stxxl containers.
  • Fixing bugs and warnings on 32-bit systems (yes, they still exist).
  • Use atomic_counted_object in class file for request reference counting.
  • Adding support for MinGW-w64 (64-bit) systems with working SJLJ thread implementations.

See the CHANGELOG for further minor changes.


First slide of the talk showing the inside of a hard disk

Recording of a Talk "STXXL 1.4.0 and Beyond"

Posted on 2014-06-22 20:00 by Timo Bingmann at Permlink with 0 Comments. Tags: #c++ #stxxl #talk #frontpage

This is a recording of a talk that I gave last week at the 3rd LSDMA Topical Meeting in Berlin. The talk covers a basic introduction into the STXXL library's features and contains many short code examples that serve as a tutorial.

The slides of the presentation 2014-06-22 STXXL 1.4.0 and Beyond.pdf 2014-06-22 STXXL 1.4.0 and Beyond.pdf are available online and the recorded talk can be seen on Youtube video below.

Download 2014-06-22 STXXL 1.4.0 and Beyond.pdf

And here is the video of the recording: https://www.youtube.com/watch?v=UswxcAOJKBE

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STXXL simple logo

Released STXXL 1.4.0

Posted on 2013-12-12 16:50 by Timo Bingmann at Permlink with 0 Comments. Tags: #c++ #university #stxxl

STXXL is an implementation of the C++ standard template library STL for external memory (out-of-core) computations, i.e., STXXL implements containers and algorithms that can process huge volumes of data that only fit on disks. While the compatibility to the STL supports ease of use and compatibility with existing applications, another design priority is high performance.

The project was originally created by Roman Dementiev and Peter Sanders at MPI Informatik in Saarbrücken. It moved to Karlsruhe with them in 2004. After Roman's PhD defense, there was a cooperation with the Algorithm Engineering group at the University of Frankfurt to create better parallel asynchronous sorting. Afterwards, stewardship moved to Frankfurt, where work on flash/SSD drives and various external memory graph algorithms was done.

After a longer stretch without further work, I have decided to take part in future development as a maintainer. This is partly due to my previous experience with it while implement in eSAIS, the external memory suffix and LCP array construction algorithm. And thus, today, the first release of the new 1.4 branch was published:

What's new in 1.4.0 ?

  • reorganized source hierarchy into include/ lib/ tests/ examples/ doc/ tools/
  • CMake build system for cross-platform compilation
  • greatly improved documentation with tutorials and examples
  • efficient external matrix operations
  • new containers stxxl::sequence and stxxl::sorter
  • improved .stxxl disk configuration files and additional options
  • combined stxxl_tool of disk benchmarks
  • simple examples and skew3 as real-world stream application
  • support for Visual Studio 2012 and 2013 without Boost
  • important bug fixes in stxxl::queue and stxxl::priority_queue

Example of the Inducing Process

eSAIS - Inducing Suffix and LCP Arrays in External Memory

Posted on 2012-11-19 15:49 by Timo Bingmann at Permlink with 2 Comments. Tags: #research #stringology #stxxl #c++

This web page accompanies our conference paper "Inducing Suffix and LCP Arrays in External Memory", which we presented at the Workshop on Algorithm Engineering and Experiments (ALENEX 2013). A PDF of the publication is available from this site as alenex13esais.pdf alenex13esais.pdf or from the online proceedings. The paper was joint work with my colleagues Johannes Fischer and Vitaly Osipov.

Download alenex13esais.pdf

The slides to my presentation of the paper on January 7th, 2013 in New Orleans, LA, USA is available: alenex13esais-slides.pdf alenex13esais-slides.pdf. They contain little text and an example of the eSAIS algorithm with a simplified PQ.

Download alenex13esais-slides.pdf

We have also submitted a full version of the eSAIS paper to a journal. Due to long publication cycles, we make a pre-print of the journal article is available here: esais-preprint.pdf esais-preprint.pdf. The full paper contains more details on the inducing algorithm for the LCP array and additional experimental details.

Download esais-preprint.pdf

Our implementations of eSAIS, the eSAIS-LCP variants, DC3 and DC3-LCP algorithms as described in the paper are available below under the GNU General Public License v3 (GPL).

eSAIS and DC3 with LCP version 0.5.4 (current) updated 2013-12-13
Source code archive:
(includes STXXL 1.4.0)
eSAIS-DC3-LCP-0.5.4.tar.bz2 eSAIS-DC3-LCP-0.5.4.tar.bz2 (1.37 MiB) Browse online
Git repositories Suffix and LCP construction algorithms
git clone https://github.com/bingmann/eSAIS
cd eSAIS; git submodule init; git submodule update
STXXL 1.4.0
git clone https://github.com/stxxl/stxxl

For more information about compiling and testing the implementation, please refer to the README included in the source.

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