187 citations · 1k across the 59 of their papers we have counts for
7 papers · 1 filter
RDMA-Based Algorithms for Sparse Matrix Multiplication on GPUs
Benjamin Brock, Aydın Buluç, Katherine Yelick
Sparse matrix multiplication is an important kernel for large-scale graph processing and other data-intensive applications. In this paper, we implement various asynchronous, RDMA-b…
Distributed Matrix-Based Sampling for Graph Neural Network Training
Alok Tripathy, Katherine Yelick, Aydin Buluc
Graph Neural Networks (GNNs) offer a compact and computationally efficient way to learn embeddings and classifications on graph data. GNN models are frequently large, making distri…
Fast multiplication of random dense matrices with fixed sparse matrices
Tianyu Liang, Riley Murray, Aydın Buluç +1
This work focuses on accelerating the multiplication of a dense random matrix with a (fixed) sparse matrix, which is frequently used in sketching algorithms. We develop a novel sch…
CPMA: An Efficient Batch-Parallel Compressed Set Without Pointers
Brian Wheatman, Randal Burns, Aydın Buluç +1
This paper introduces the batch-parallel Compressed Packed Memory Array (CPMA), a compressed, dynamic, ordered set data structure based on the Packed Memory Array (PMA). Traditiona…
Space Efficient Sequence Alignment for SRAM-Based Computing: X-Drop on the Graphcore IPU
Luk Burchard, Max Xiaohang Zhao, Johannes Langguth +2
Dedicated accelerator hardware has become essential for processing AI-based workloads, leading to the rise of novel accelerator architectures. Furthermore, fundamental differences…
Extreme-scale many-against-many protein similarity search
Oguz Selvitopi, Saliya Ekanayake, Giulia Guidi +7
Similarity search is one of the most fundamental computations that are regularly performed on ever-increasing protein datasets. Scalability is of paramount importance for uncoverin…