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The Sampled Dense-Dense Matrix Multiplication (SDDMM) represents a foundational operation crucial for numerous significant machine learning factor analysis algorithms. Among these algorithms are Alternating Least Squares (ALS), Latent Dirichlet Allocation (LDA), Sparse Factor Analysis (SFA), and Gama Poisson. In this repository, we present both our code and the comprehensive findings detailed in ourfinal report. Our focus lies on the development ofGPU-Dynamic, an efficient GPU-based implementation of the SDDMM kernel. Our solution boasts remarkable performance enhancements, surpassing current implementations found in Torch with notable speedups of up to 100x. Furthermore, our implementation delivers competitive outcomes when compared to DGL.

At the bottom of this README is a representation of all matrices that we have used for evaluation. The matrices range different dimensions as well as different densities. All matrices originate from theSuiteSparse Matrix Collection and can be downloaded by executing theinstall_matrices.sh script.

To run the code, you need to install LibTorch for C++ which cou can download fromhere. We recommend usingPyTorch >= 2.1.0 andCUDA >= 12.1. In addition you should havegcc >= 10.2.0 andcmake >= 3.21 installed.

Make sure to update therun_cmake.sh file by updating the path to yourlibtorch library. You can finally compile and run the code by executing

./run_cmake.sh./build/src/dphpc --K 32 --data_folder data/

Matrix	Rows	Cols	Non-Zero	Density	Image
Fluid	656	656	18,964	4.4%
Oil	66	66	4,356	100%
Biochemical	1,922	1,922	4,335	0.1%
Circuit	1,220	1,220	5,860	0.39%
Heat	1,794	1,794	7,764	0.24%
Mass	420	420	7,860	4.45%
Adder	1,813	1,813	11,246	0.34%
Trackball	25,503	25,503	15,525	0.01%

Matrix	Rows	Cols	Non-Zero	Density	Image
Human Gene 2	14,340	14,340	18,068,388	8.8%
ND12k	36,000	36,000	14,220,946	1%
Mix	29,957	29,957	1,990,919	0.22%
Mecanics	29,067	29,067	2,081,063	0.24%
Power	8,140	8,140	2,012,833	3.03%
Combinatorics	4,562	5,761	2,462,970	9.37%
Stress	25,710	25,710	3,749,582	0.56%
Mouse	45,101	45,101	28,967,291	1.42%

Matrix	Rows	Cols	Non-Zero	Density	Image
Email enron	36,692	36,692	367,662	0.027%
Boeing	52,329	52,329	2,600,295	0.09%
Boeing Diagonal	217,918	217,918	11,524,432	0.02%
Stiffness	503,712	503,712	36,816,170	0.014%
Semi conductor	1,090,664	1,090,664	34,767,207	0.0029%
VLSI	1,453,908	1,453,908	37,475,646	0.0017%
Stack overflow	2,601,977	2,601,977	36,233,450	0.00053%
Chip	2,987,012	2,987,012	26,621,983	0.00029%