483 citations · 1k across the 69 of their papers we have counts for
24 papers · 1 filter
High Performance Unstructured SpMM Computation Using Tensor Cores
Patrik Okanovic, Grzegorz Kwasniewski, Paolo Sylos Labini +3
High-performance sparse matrix-matrix (SpMM) multiplication is paramount for science and industry, as the ever-increasing sizes of data prohibit using dense data structures. Yet, e…
Low-Depth Spatial Tree Algorithms
Yves Baumann, Tal Ben-Nun, Maciej Besta +3
Contemporary accelerator designs exhibit a high degree of spatial localization, wherein two-dimensional physical distance determines communication costs between processing elements…
Arrow Matrix Decomposition: A Novel Approach for Communication-Efficient Sparse Matrix Multiplication
Lukas Gianinazzi, Alexandros Nikolaos Ziogas, Langwen Huang +9
We propose a novel approach to iterated sparse matrix dense matrix multiplication, a fundamental computational kernel in scientific computing and graph neural network training. In…
ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations
Maciej Besta, Cesare Miglioli, Paolo Sylos Labini +11
Important graph mining problems such as Clustering are computationally demanding. To significantly accelerate these problems, we propose ProbGraph: a graph representation that enab…
Asynchronous Distributed-Memory Triangle Counting and LCC with RMA Caching
András Strausz, Flavio Vella, Salvatore Di Girolamo +2
Triangle count and local clustering coefficient are two core metrics for graph analysis. They find broad application in analyses such as community detection and link recommendation…
On the Parallel I/O Optimality of Linear Algebra Kernels: Near-Optimal Matrix Factorizations
Grzegorz Kwasniewski, Marko Kabić, Tal Ben-Nun +8
Matrix factorizations are among the most important building blocks of scientific computing. State-of-the-art libraries, however, are not communication-optimal, underutilizing curre…
GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebra
Maciej Besta, Zur Vonarburg-Shmaria, Yannick Schaffner +16
We propose GraphMineSuite (GMS): the first benchmarking suite for graph mining that facilitates evaluating and constructing high-performance graph mining algorithms. First, GMS com…
The Future is Big Graphs! A Community View on Graph Processing Systems
Sherif Sakr, Angela Bonifati, Hannes Voigt +38
Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users a…
SeBS: A Serverless Benchmark Suite for Function-as-a-Service Computing
Marcin Copik, Grzegorz Kwasniewski, Maciej Besta +2
Function-as-a-Service (FaaS) is one of the most promising directions for the future of cloud services, and serverless functions have immediately become a new middleware for buildin…
To Push or To Pull: On Reducing Communication and Synchronization in Graph Computations
Maciej Besta, Michal Podstawski, Linus Groner +2
We reduce the cost of communication and synchronization in graph processing by analyzing the fastest way to process graphs: pushing the updates to a shared state or pulling the upd…
Accelerating Irregular Computations with Hardware Transactional Memory and Active Messages
Maciej Besta, Torsten Hoefler
We propose Atomic Active Messages (AAM), a mechanism that accelerates irregular graph computations on both shared- and distributed-memory machines. The key idea behind AAM is that…
Substream-Centric Maximum Matchings on FPGA
Maciej Besta, Marc Fischer, Tal Ben-Nun +3
Developing high-performance and energy-efficient algorithms for maximum matchings is becoming increasingly important in social network analysis, computational sciences, scheduling,…
High-Performance Distributed RMA Locks
Patrick Schmid, Maciej Besta, Torsten Hoefler
We propose a topology-aware distributed Reader-Writer lock that accelerates irregular workloads for supercomputers and data centers. The core idea behind the lock is a modular desi…
SlimSell: A Vectorizable Graph Representation for Breadth-First Search
Maciej Besta, Florian Marending, Edgar Solomonik +1
Vectorization and GPUs will profoundly change graph processing. Traditional graph algorithms tuned for 32- or 64-bit based memory accesses will be inefficient on architectures with…
Evaluating the Cost of Atomic Operations on Modern Architectures
Hermann Schweizer, Maciej Besta, Torsten Hoefler
Atomic operations (atomics) such as Compare-and-Swap (CAS) or Fetch-and-Add (FAA) are ubiquitous in parallel programming. Yet, performance tradeoffs between these operations and va…
Fault Tolerance for Remote Memory Access Programming Models
Maciej Besta, Torsten Hoefler
Remote Memory Access (RMA) is an emerging mechanism for programming high-performance computers and datacenters. However, little work exists on resilience schemes for RMA-based appl…
On the Parallel I/O Optimality of Linear Algebra Kernels: Near-Optimal LU Factorization
Grzegorz Kwasniewski, Tal Ben-Nun, Alexandros Nikolaos Ziogas +3
Dense linear algebra kernels, such as linear solvers or tensor contractions, are fundamental components of many scientific computing applications. In this work, we present a novel…
Enabling Highly-Scalable Remote Memory Access Programming with MPI-3 One Sided
Robert Gerstenberger, Maciej Besta, Torsten Hoefler
Modern interconnects offer remote direct memory access (RDMA) features. Yet, most applications rely on explicit message passing for communications albeit their unwanted overheads.…
Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems
Maciej Besta, Marc Fischer, Vasiliki Kalavri +2
Graph processing has become an important part of various areas of computing, including machine learning, medical applications, social network analysis, computational sciences, and…
Active Access: A Mechanism for High-Performance Distributed Data-Centric Computations
Maciej Besta, Torsten Hoefler
Remote memory access (RMA) is an emerging high-performance programming model that uses RDMA hardware directly. Yet, accessing remote memories cannot invoke activities at the target…
Graph Processing on FPGAs: Taxonomy, Survey, Challenges
Maciej Besta, Dimitri Stanojevic, Johannes De Fine Licht +2
Graph processing has become an important part of various areas, such as machine learning, computational sciences, medical applications, social network analysis, and many others. Va…
A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning
Tal Ben-Nun, Maciej Besta, Simon Huber +3
We introduce Deep500: the first customizable benchmarking infrastructure that enables fair comparison of the plethora of deep learning frameworks, algorithms, libraries, and techni…
Transformations of High-Level Synthesis Codes for High-Performance Computing
Johannes de Fine Licht, Maciej Besta, Simon Meierhans +1
Spatial computing architectures promise a major stride in performance and energy efficiency over the traditional load/store devices currently employed in large scale computing syst…
Scaling betweenness centrality using communication-efficient sparse matrix multiplication
Edgar Solomonik, Maciej Besta, Flavio Vella +1
Betweenness centrality (BC) is a crucial graph problem that measures the significance of a vertex by the number of shortest paths leading through it. We propose Maximal Frontier Be…