33 citations · 36 across the 6 of their papers we have counts for
6 papers
MAGNUS: Fast SpGEMM on GPUs for Irregular Matrices via Hierarchical Multisplit
Jordi Wolfson-Pou, Ahmed Helal, Fabrizio Petrini
We present MAGNUS, a novel algorithm for sparse matrix-matrix multiplication (SpGEMM) of irregular matrices on GPUs. Such matrices often contain many heavy rows, those with larg…
ReLATE: Accelerating Tensor Decomposition via Safe and Efficient Learning of Sparse Encodings
Ahmed E. Helal, Fabio Checconi, Jan Laukemann +4
Tensor decomposition (TD) is essential for analyzing high-dimensional sparse data, yet its irregular computations and memory-access patterns pose major performance challenges on mo…
Accelerating Sparse Tensor Decomposition Using Adaptive Linearized Representation
Jan Laukemann, Ahmed E. Helal, S. Isaac Geronimo Anderson +7
High-dimensional sparse data emerge in many critical application domains such as healthcare and cybersecurity. To extract meaningful insights from massive volumes of these multi-di…
Efficient, Out-of-Memory Sparse MTTKRP on Massively Parallel Architectures
Andy Nguyen, Ahmed E. Helal, Fabio Checconi +6
Tensor decomposition (TD) is an important method for extracting latent information from high-dimensional (multi-modal) sparse data. This study presents a novel framework for accele…
ALTO: Adaptive Linearized Storage of Sparse Tensors
Ahmed E. Helal, Jan Laukemann, Fabio Checconi +4
The analysis of high-dimensional sparse data is becoming increasingly popular in many important domains. However, real-world sparse tensors are challenging to process due to their…
DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings
Muhammad Abdul-Mageed, Shady Elbassuoni, Jad Doughman +7
Word embeddings are a core component of modern natural language processing systems, making the ability to thoroughly evaluate them a vital task. We describe DiaLex, a benchmark for…