Datasets
The data is coming from https://sparse.tamu.edu/, our commonly used datasets are listed in table 1.
Datasets | Vertex | Edges | Degree |
---|---|---|---|
as-Skitter | 1694616 | 11094209 | 6.546739202 |
coPapersDBLP | 540486 | 15245729 | 28.20744478 |
coPapersCiteseer | 434102 | 16036720 | 36.94228545 |
cit-Patents | 3774768 | 16518948 | 4.37614921 |
europe_osm | 50912018 | 54054660 | 1.061726919 |
hollywood | 1139905 | 57515616 | 50.45649945 |
soc-LiveJournal1 | 4847571 | 68993773 | 14.23264827 |
ljournal-2008 | 5363260 | 79023142 | 14.73416206 |
patients | 1250000 | 200 |
Performance
For representing the resource utilization in each benchmark, we separate the overall utilization into 2 parts, where P stands for the resource usage in platform, that is those instantiated in static region of the FPGA card, as well as K represents those used in kernels (dynamic region). The input is directed or undirected graph in compressed sparse row (CSR) format, and the target device is set to Alveo U50/U250.
Architecture | Dataset | Latency(s) | Timing | LUT(P/K) | BRAM(P/K) | URAM(P/K) | DSP(P/K) |
---|---|---|---|---|---|---|---|
Single Source Shortest Path (Directed, U250) | soc-LiveJournal1 | 25.94 | 300MHz | 108.1K/21.1K | 178/127 | 0/20 | 4/2 |
Connected Component (Directed/Undirected, U250) | coPapersCiteseer | 1.811 | 280MHz | 101.7K/101.5K | 165/387 | 0/112 | 4/3 |
Strongly Connected Component (Directed/Undirected, U250) | ljournal-2008 | 3.484 | 275MHz | 101.7K/160.5K | 165/523.5 | 0/110 | 4/6 |
Triangle Counting (Undirected, U250) | europe_osm | 1.08 | 300MHz | 150.9K/20.5K | 338/62 | 0/16 | 7/0 |
Label Propagation (Directed, U250) | hollywood | 107.39 | 292MHz | 158.2K/71.0K | 375/100 | 0/0 | 7/0 |
PageRank (Directed, U250, Cache 1) | europe_osm | 47.376 | 300MHz | 154.6K/252.9K | 357/546 | 0/0 | 7/52 |
PageRank (Directed, U250, Cache 32K) | europe_osm | 51.919 | 225MHz | 156.4K/100.4K | 357/189 | 0/224 | 7/52 |
PageRank MultiChannels (Directed, U50) | europe_osm | 34.26 | 229MHz | 118.8K/132.0K | 178/303 | 0/224 | 4/84 |
General Similarity Cosine (Undirected, U50) | as-Skitter | 0.0213 | 295MHz | 121.1K/164.6K | 180/230.5 | 0/80 | 4/645 |
Sparse Similarity Cosine (Directed/Undirected, U50) | coPaperDBLP | 0.0137 | 295MHz | 132.8K/120.1K | 180/310.5 | 0/128 | 4/127 |
Dense Similarity Cosine (Directed/Undirected, U50) | patients | 0.0112 | 260MHz | 119.1K/266.1K | 180/618 | 0/48 | 4/2364 |
Two Hop Path Count (Directed, u50) | soc-LiveJournal1 | 38.90 | 300MHz | 145.9K/34.1K | 180/210 | 0/0 | 4/0 |
Louvain modularity fast (Undirected, u50) | europe_osm | 111.092 | 188.3MHz | 123.4K/127.6K | 180/461 | 0/208 | 4/115 |
Renumber (Undirected, u50) | europe.txt | 5.22 | 240.3MHz | 103.7K/21.6K | 178/27 | 0/256 | 4/0 |
Merge (Undirected u50) | cit-Patents | 0.82 | 240.0MHz | 112.9K/40.6K | 178/73 | 0/163 | 4/0 |
These are details for benchmark result and usage steps.
Test Overview
Here are benchmarks of the Vitis Graph Library using the Vitis environment and comparing with Spark(v3.0.0) and Tigergraph(v2.4.0).
Spark
- Spark 3.0.0 installed and configured.
- Spark running on platform with Intel(R) Xeon(R) CPU E5-2690 v4 @2.600GHz, 56 Threads (2 Sockets, 14 Core(s) per socket, 2 Thread(s) per core).
Tigergraph
- Tigergraph 2.4.1 installed and configured.
- Tigergraph running on platform with Intel(R) Xeon(R) CPU E5-2640 v3 @2.600GHz, 32 Threads (16 Core(s)).
- Download code
These graph benchmarks can be downloaded from vitis libraries main
branch.
git clone https://github.com/Xilinx/Vitis_Libraries.git cd Vitis_Libraries git checkout main cd graph
- Setup environment
Specifying the corresponding Vitis, XRT, and path to the platform repository by running following commands.
source <intstall_path>/installs/lin64/Vitis/2022.1/settings64.sh source /opt/xilinx/xrt/setup.sh export PLATFORM_REPO_PATHS=/opt/xilinx/platforms