We present a C++ header-only parallel sparse matrix library, based on sparse quadtree representation of matrices using the Chunks and Tasks programming model. The library implements a number of sparse matrix algorithms for distributed memory parallelization that are able to dynamically exploit data locality to avoid movement of data. This is demonstrated for the example of block-sparse matrix-matrix multiplication applied to three sequences of matrices with different nonzero structure, using the CHT-MPI 2.0 runtime library implementation of the Chunks and Tasks model. The runtime library succeeds to dynamically load balance the calculation regardless of the sparsity structure.

中文翻译：

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块和任务矩阵库2.0

我们基于Chunk and Tasks编程模型，基于矩阵的稀疏四叉树表示形式，提供了一个仅C ++头并行稀疏矩阵库。该库为分布式内存并行化实现了许多稀疏矩阵算法，这些算法能够动态利用数据局部性来避免数据移动。使用块和任务模型的CHT-MPI 2.0运行时库实现，将块稀疏矩阵矩阵乘法应用于具有不同非零结构的三个矩阵序列的示例对此进行了演示。无论稀疏结构如何，运行时库都能成功地动态平衡计算的负载。