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12/22/2022
Accelerating Barnes-Hut t-SNE Algorithm by Efficient Parallelization on Multi-Core CPUs
t-SNE remains one of the most popular embedding techniques for visualizi...
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11/11/2022
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling
Training Graph Neural Networks, on graphs containing billions of vertice...
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04/16/2021
Efficient and Generic 1D Dilated Convolution Layer for Deep Learning
Convolutional neural networks (CNNs) have found many applications in tas...
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04/14/2021
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks
Full-batch training on Graph Neural Networks (GNN) to learn the structur...
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04/12/2021
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads
During the past decade, novel Deep Learning (DL) algorithms/workloads an...
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07/13/2020
Deep Graph Library Optimizations for Intel(R) x86 Architecture
The Deep Graph Library (DGL) was designed as a tool to enable structure ...
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06/23/2020
Benchmarking Learned Indexes
Recent advancements in learned index structures propose replacing existi...
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10/10/2019
LISA: Towards Learned DNA Sequence Search
Next-generation sequencing (NGS) technologies have enabled affordable se...
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07/27/2019
