Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...

Here is a blueprint for architecting real-time systems that scale without sacrificing speed. A common mistake I see in early-stage personalization teams is trying to rank every item in the catalog in ...

A real-world matrix (1138_bus.mtx) is used to benchmark performance across different execution models. ├── CMakeLists.txt ├── include/ │ ├── csr_matrix.hpp │ ├── csr_operations.hpp │ └── ...

Abstract: Sparse-sparse matrix multiplication (SpGEMM) is a well-studied problem on CPUs, GPUs, accelerators (e.g. FPGAs), and distributed systems. The main computational bottleneck in SpGEMM is the ...

Since our sparse attention is implemented by FlexAttention, we recommend conducting a warm-up inference first, as subsequent inferences will perform better in terms of speed. To better demonstrate the ...