#sparse #opencl #cuda #equation #matrix-multiplication

RayBNN_Sparse

Sparse Matrix Library for GPUs, CPUs, and FPGAs via CUDA, OpenCL, and oneAPI

7 releases (2 stable)

2.0.2 Jun 18, 2024
2.0.1 Jun 5, 2024
0.1.5 Nov 6, 2023
0.1.4 Oct 29, 2023
0.1.0 Sep 5, 2023

#241 in Math

Download history 6/week @ 2024-03-10 3/week @ 2024-03-17 10/week @ 2024-03-24 16/week @ 2024-03-31 1/week @ 2024-04-07 7/week @ 2024-05-19 2/week @ 2024-05-26 147/week @ 2024-06-02 12/week @ 2024-06-09 154/week @ 2024-06-16 6/week @ 2024-06-23

433 downloads per month
Used in 3 crates

GPL-3.0-only

46KB
964 lines

RayBNN_Sparse

Sparse Matrix Library for GPUs, CPUs, and FPGAs via CUDA, OpenCL, and oneAPI

Supports CSR, COO, CSC, and block sparse matrices

Requires Arrayfire and Arrayfire Rust

Supports f16, f32, f64, Complexf16, Complexf32, Complexf64

Install Arrayfire

Install the Arrayfire 3.9.0 binaries at https://arrayfire.com/binaries/

or build from source https://github.com/arrayfire/arrayfire/wiki/Getting-ArrayFire

Add to your Cargo.toml

arrayfire = { version = "3.8.1", package = "arrayfire_fork" }
num = "0.4.1"
num-traits = "0.2.16"
half = { version = "2.3.1" , features = ["num-traits"] }
RayBNN_Sparse = "2.0.2"

List of Examples

Convert COO to CSR Sparse Matrix

let mut WRowIdxCSR = RayBNN_Sparse::Util::Convert::COO_to_CSR(&WRowIdxCOO,7);

Convert CSR to COO Sparse Matrix

let mut WRowIdxCOO = RayBNN_Sparse::Util::Convert::CSR_to_COO(&WRowIdxCSR);

Search COO Matrix for value

let valsel = RayBNN_Sparse::Util::Search::COO_find(&WRowIdxCOO,&idxsel);

Batch Search COO Matrix for value

let valsel = RayBNN_Sparse::Util::Search::COO_batch_find(&WRowIdxCOO,&idxsel,4);

Get global index

let global_idx = RayBNN_Sparse::Util::Convert::get_global_weight_idx(
    2000, 
    &WRowIdxCOO, 
    &WColIdx
);

Get global index 2

let global_idx = RayBNN_Sparse::Util::Convert::get_global_weight_idx2(
    2000, 
    &WRowIdxCOO, 
    &WColIdx
);

Clear inputs to weighted adjancency matrix

RayBNN_Sparse::Util::Remove::clear_input::<f32>(
    &mut WValues,
    &mut WRowIdxCOO,
    &mut WColIdx,
    3
);

Clear output of the weighted adjancency matrix

RayBNN_Sparse::Util::Remove::clear_output::<f32>(
    &mut WValues,
    &mut WRowIdxCOO,
    &mut WColIdx,
    7-2
);

Clear input to hidden neurons of the weighted adjancency matrix

RayBNN_Sparse::Util::Remove::clear_input_to_hidden::<f64>(
    &mut WValues,
    &mut WRowIdxCOO,
    &mut WColIdx,
    3
);

Delete the smallest weights in the weighted adjancency matrix

RayBNN_Sparse::Util::Remove::delete_smallest_weights::<f32>(
    &mut WValues,
    &mut WRowIdxCOO,
    &mut WColIdx,
    3
);

Delete the smallest weights with a random probability in the weighted adjancency matrix

RayBNN_Sparse::Util::Remove::delete_weights_with_prob::<f64>(
    &mut WValues,
    &mut WRowIdxCOO,
    &mut WColIdx,
    3
);

Remap rows in weighted adjancency matrix

let valsel = RayBNN_Sparse::Util::Convert::remap_rows(&dictionary, &idx,1000);

Block Matrix Multiplication

RayBNN_Sparse::Matrix::Block::matmul::<f64>(
	&input_start,
    &input_end,

    &block_start,
    &block_end,


    &input,
    &block
);

Transpose Block Matrix Multiplication

RayBNN_Sparse::Matrix::Block::trans_matmul::<f64>(
	&input_start,
    &input_end,

    &block_start,
    &block_end,


    &input,
    &block
);

Parallel lookup of Arrays

let result =  RayBNN_Sparse::Util::Search::parallel_lookup(
    0,
    1,

    &idx_arr,
    &test_arr,
);

Dependencies

~7MB
~140K SLoC