Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Understanding the Design-Space of Sparse/Dense Multiphase GNN dataflows
  on Spatial Accelerators   Graph Neural Networks (GNNs) have garnered a lot of recent interest because
of their success in learning representations from graph-structured data across
several critical applications in cloud and HPC. Owing to their unique compute
and memory characteristics that come from an interplay between dense and sparse
phases of computations, the emergence of reconfigurable dataflow (aka spatial)
accelerators offers promise for acceleration by mapping optimized dataflows
(i.e., computation order and parallelism) for both phases. The goal of this
work is to characterize and understand the design-space of dataflow choices for
running GNNs on spatial accelerators in order for mappers or design-space
exploration tools to optimize the dataflow based on the workload. Specifically,
we propose a taxonomy to describe all possible choices for mapping the dense
and sparse phases of GNN inference, spatially and temporally over a spatial
accelerator, capturing both the intra-phase dataflow and the inter-phase
(pipelined) dataflow. Using this taxonomy, we do deep-dives into the cost and
benefits of several dataflows and perform case studies on implications of
hardware parameters for dataflows and value of flexibility to support pipelined
execution.

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The categories of this paper are: math
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The categories of this paper are: stat
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The categories of this paper are: physics
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
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The categories of this paper are: eess
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The categories of this paper are: adap-org
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The categories of this paper are: bayes-an
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The categories of this paper are: patt-sol
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The categories of this paper are: alg-geom
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The categories of this paper are: hep-ex
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-ex
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The categories of this paper are: dg-ga
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The categories of this paper are: gr-qc
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The categories of this paper are: supr-con