Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the widely-used, memory-bound Sparse ...

The aim of this study was to integrate the simplicity of structured sparsity into existing vector execution flow and vector processing units (VPUs), thus expediting the corresponding matrix ...

Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...

The most widely used matrix-matrix multiplication routine is GEMM (GEneral Matrix Multiplication) from the BLAS (Basic Linear Algebra Subroutines) library. And these days it can be found being used in ...

Image Matrix Transformations If A is a 3 × 3 matrix then we can apply a linear transformation to each rgb vector via matrix multiplication, where [r, g, b] are the original values and [r ′, g ′, b ′] ...

Since a vector is essentially a contiguous array of real numbers, and the computer memory is a contiguous array of bytes, the mapping of the elements of a vector onto the C++ array and then to the ...