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Presentations
IPDPS 2020, Dynamic Graphs on the GPU, May 2020. [slides | video]
FOSDEM 2020, Gunrock: High-Performance Graph Analytics for the GPU, Feb 2020. [slides | video]
GrAPL 2019, Graph Coloring on the GPU, May 2019. [slides]
GTC 2018, Latest Development of the Gunrock Graph Processing Library on GPUs, March 2018. [slides | video]
GTC 2018, Writing Graph Primitives with Gunrock, March 2018. [slides | video]
GTC 2016, Gunrock: A Fast and Programmable Multi-GPU Graph Processing Library, April 2016. [slides]
NVIDIA webinar, April 2016. [slides]
GPU Technology Theater at SC15, Gunrock: A Fast and Programmable Multi-GPU Graph processing Library, November 2015. [slides | video]
GTC 2014, High-Performance Graph Primitives on the GPU: design and Implementation of Gunrock, March 2014. [slides | video]
Essentials © 2022 The Regents of the University of California
- Programming Model
- Gunrock Operators
- Graph Algorithms
- Getting Essentials
- (GitHub Template)
essentialsproject example
- MGPU, Python, Docs (needs review)
- Boolmap Frontier
- Hypergraphs (private)
- Modern CPP Features
- Programming Interface Examples (API)
- Style Guide
- Understanding the code structure
- Git Workflow
-
Debugging with
cuda-memcheckandcuda-gdb - Profiling with NVIDIA Nsight Systems and Compute
- Unit testing with GoogleTest
- Performance analysis
- How to write a new graph algorithm
- PageRank: PageRank: From
networkxtogunrock essentials - How to write parallel operators
- How to add a new graph representation
- How to add a new frontier representation
- How to add multiple GPU support
- How to bind an application to python
- How to use
thrust/cub
- Writing sparse-matrix dense-vector multiplication using graphs
- Variadic Inheritance
- Polymorphic-Virtual (Diamond) Inheritance
- Need for custom copy constructor
- CUDA-enabled
std::shared_ptr
- Ubuntu
-latest - Windows
-latest - Doxygen
- Code Quality