arXiv subjects

Matthias Schimek

Publications and source records attributed to Matthias Schimek.

8 recordsLinked to original sources

arXiv2026

Concepts in Practice: C++ MPI Bindings for the HPC Ecosystem. From a Standardizable Core to a Composable Interface

The official C++ MPI bindings were removed from the standard in 2008, leaving a gap that numerous third-party libraries have attempted to fill. However, existing wrappers typically cover only a limited subset of MPI or target specific use cases, falling short of a general-purpose solution. A recent conceptual paper proposed general design principles for modern C++ bindings based on C++20 concepts, without committing to a concrete interface. We present the first concrete realization of these principles in a layered architecture. At the foundation, we define a core layer: refined C++20 concepts formalizing the MPI standard's notion of data buffers, automatic mapping of standard C++ constructs, non-intrusive customization points for third-party types, and concept-based wrappers for MPI procedures. The result is a low-level native C++ MPI interface that works directly with STL containers, is highly extensible, and lends itself to standardization. Built on this core, we present KaMPIng-v2 -- a C++ MPI library offering the convenience and memory-safety of KaMPIng with composable, pipe-based syntax inspired by C++ ranges for efficient, boilerplate-free MPI programming. Finally, we demonstrate the core layer's broad applicability by designing lightweight adapters for GPU and performance-portability libraries, making the HPC ecosystem a first-class citizen in MPI. Kokkos views, Thrust device vectors, and SYCL buffers can be passed directly to MPI procedures, with adapter logic remaining self-contained. All contributions are backed by a fully functional open-source reference implementation, demonstrating the practical viability of the proposed design.

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arXiv2026

Engineering Scalable Distributed List Ranking

The list ranking problem is one of the classical problems of parallel computing, with nontrivial algorithms and many applications as a subroutine for solving other problems. While it has been intensively studied in the early days of parallel computing, few things happened in the last 20 years. In particular, there is little work on scaling list ranking to large machines and input sizes. We reconsider list ranking starting from the ground-breaking results of Sibeyn a quarter century ago. We employ algorithm and performance engineering to improve his sparse ruling-set algorithm, making it capable of scaling to many processors, and provide a more detailed analysis of the impact of the algorithm's parameters, further guiding our practical implementation. We perform an extensive experimental study across a variety of input instances with different structural properties. We demonstrate that indirect communication, exploiting input locality, and message coalescing allows scaling to billions of elements on up to 24,576 cores.

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arXiv2025

Concepts for designing modern C++ interfaces for MPI

Since the C++ bindings were deleted in 2008, the Message Passing Interface (MPI) community has revived efforts in building high-level modern C++ interfaces. Such interfaces are either built to serve specific scientific application needs (with limited coverage to the underlying MPI functionalities), or as an exercise in general-purpose programming model building, with the hope that bespoke interfaces can be broadly adopted to construct a variety of distributed-memory scientific applications. However, with the advent of modern C++-based heterogeneous programming models, GPUs and widespread Machine Learning (ML) usage in contemporary scientific computing, the role of prospective community-standardized high-level C++ interfaces to MPI is evolving. The success of such an interface clearly will depend on providing robust abstractions and features adhering to the generic programming principles that underpin the C++ programming language, without compromising on either performance and portability, the core principles upon which MPI was founded. However, there is a tension between idiomatic C++ handling of types and lifetimes and MPI's loose interpretation of object lifetimes/ownership and insistence on maintaining global states. Instead of proposing "yet another" high-level C++ interface to MPI, overlooking or providing partial solutions to work around the key issues concerning the dissonance between MPI semantics and idiomatic C++, this paper focuses on the three fundamental aspects of a high-level interface: type system, object lifetimes and communication buffers, also identifying inconsistencies in the MPI specification. Presumptive solutions can be unrefined, and we hope the broader MPI and C++ communities will engage with us in productive exchange of ideas and concerns.

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arXiv2024

Fast and Lightweight Distributed Suffix Array Construction -- First Results

We present first algorithmic ideas for a practical and lightweight adaption of the DCX suffix array construction algorithm [Sanders et al., 2003] to the distributed-memory setting. Our approach relies on a bucketing technique which enables a lightweight implementation which uses less than half of the memory required by the currently fastest distributed-memory suffix array algorithm PSAC [Flick and Aluru, 2015] while being competitive or even faster in terms of running time.

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arXiv2024

KaMPIng: Flexible and (Near) Zero-Overhead C++ Bindings for MPI

The Message-Passing Interface (MPI) and C++ form the backbone of high-performance computing, but MPI only provides C and Fortran bindings. While this offers great language interoperability, high-level programming languages like C++ make software development quicker and less error-prone. We propose novel C++ language bindings that cover all abstraction levels from low-level MPI calls to convenient STL-style bindings, where most parameters are inferred from a small subset of parameters, by bringing named parameters to C++. This enables rapid prototyping and fine-tuning runtime behavior and memory management. A flexible type system and additional safety guarantees help to prevent programming errors. By exploiting C++'s template metaprogramming capabilities, this has (near) zero overhead, as only required code paths are generated at compile time. We demonstrate that our library is a strong foundation for a future distributed standard library using multiple application benchmarks, ranging from text-book sorting algorithms to phylogenetic interference.

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arXiv2024

Scalable Distributed String Sorting

String sorting is an important part of tasks such as building index data structures. Unfortunately, current string sorting algorithms do not scale to massively parallel distributed-memory machines since they either have latency (at least) proportional to the number of processors $p$ or communicate the data a large number of times (at least logarithmic). We present practical and efficient algorithms for distributed-memory string sorting that scale to large $p$. Similar to state-of-the-art sorters for atomic objects, the algorithms have latency of about $p^{1/k}$ when allowing the data to be communicated $k$ times. Experiments indicate good scaling behavior on a wide range of inputs on up to 49152 cores. Overall, we achieve speedups of up to 5 over the current state-of-the-art distributed string sorting algorithms.

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arXiv2023

Engineering Massively Parallel MST Algorithms

We develop and extensively evaluate highly scalable distributed-memory algorithms for computing minimum spanning trees (MSTs). At the heart of our solutions is a scalable variant of Boruvka's algorithm. For partitioned graphs with many local edges, we improve this with an effective form of contracting local parts of the graph during a preprocessing step. We also adapt the filtering concept of the best practical sequential algorithm to develop a massively parallel Filter-Boruvka algorithm that is very useful for graphs with poor locality and high average degree. Our experiments indicate that our algorithms scale well up to at least 65 536 cores and are up to 800 times faster than previous distributed MST algorithms.

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arXiv2020

Communication-Efficient String Sorting

There has been surprisingly little work on algorithms for sorting strings on distributed-memory parallel machines. We develop efficient algorithms for this problem based on the multi-way merging principle. These algorithms inspect only characters that are needed to determine the sorting order. Moreover, communication volume is reduced by also communicating (roughly) only those characters and by communicating repetitions of the same prefixes only once. Experiments on up to 1280 cores reveal that these algorithm are often more than five times faster than previous algorithms.

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