VBCSR is a high-performance distributed sparse matrix library designed for efficiency and ease of use. It combines the speed of optimized C++ kernels with the flexibility of Python.
Understanding the benefits of matrix converters for EV chargers and a comparison of different matrix converter topologies.
Abstract: The performance of sparse matrix vector multiplication (SpMV) is important to computational scientists. Compressed sparse row (CSR) is the most frequently used format to store sparse ...
Abstract: Deep learning models rely heavily on matrix multiplication, which is computationally expensive and memory-intensive. Sparse matrices, which contain a high proportion of zero elements, offer ...
Train State transition models or pretrain State embedding models. See the State paper. See the Google Colab to train STATE for the Virtual Cell Challenge. To start an experiment, write a TOML file ...