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Automine: harmonizing high-level abstraction and high performance for graph mining
Graph mining algorithms that aim at identifying structural patterns of graphs are typically
more complex than graph computation algorithms such as breadth first search. Researchers …
more complex than graph computation algorithms such as breadth first search. Researchers …
MTM: Rethinking memory profiling and migration for multi-tiered large memory
Multi-terabyte large memory systems are often characterized by more than two memory tiers
with different latency and bandwidth. Multi-tiered large memory systems call for rethinking of …
with different latency and bandwidth. Multi-tiered large memory systems call for rethinking of …
Practical parallel hypergraph algorithms
While there has been significant work on parallel graph processing, there has been very
surprisingly little work on high-performance hypergraph processing. This paper presents a …
surprisingly little work on high-performance hypergraph processing. This paper presents a …
Atmem: Adaptive data placement in graph applications on heterogeneous memories
Active development in new memory devices, such as non-volatile memories and high-
bandwidth memories, brings heterogeneous memory systems (HMS) as a promising …
bandwidth memories, brings heterogeneous memory systems (HMS) as a promising …
iqan: Fast and accurate vector search with efficient intra-query parallelism on multi-core architectures
Vector search has drawn a rapid increase of interest in the research community due to its
application in novel AI applications. Maximizing its performance is essential for many tasks …
application in novel AI applications. Maximizing its performance is essential for many tasks …
Taming the zoo: The unified graphit compiler framework for novel architectures
We live in a new Cambrian Explosion of hardware devices. The end of conventional
processor scaling has driven research and industry practice to explore a new generation of …
processor scaling has driven research and industry practice to explore a new generation of …
Scaph: Scalable {GPU-Accelerated} Graph Processing with {Value-Driven} Differential Scheduling
We introduce Scaph, a GPU-accelerated graph system that achieves scale-up graph
processing on large-scale graphs that are initially partitioned into subgraphs at the host to …
processing on large-scale graphs that are initially partitioned into subgraphs at the host to …
Compiling graph applications for GPU s with GraphIt
The performance of graph programs depends highly on the algorithm, the size and structure
of the input graphs, as well as the features of the underlying hardware. No single set of …
of the input graphs, as well as the features of the underlying hardware. No single set of …
Feluca: A two-stage graph coloring algorithm with color-centric paradigm on GPU
There are great challenges in performing graph coloring on GPU in general. First, the long-
tail problem exists in the recursion algorithm because the conflict (ie, different threads assign …
tail problem exists in the recursion algorithm because the conflict (ie, different threads assign …
A deep dive into understanding the random walk-based temporal graph learning
Machine learning on graph data has gained significant interest because of its applicability to
various domains ranging from product recommendations to drug discovery. While there is a …
various domains ranging from product recommendations to drug discovery. While there is a …