Sentence examples for matrix multiplication algorithm from inspiring English sources

The matrix multiplication algorithm in the object-attribute distributed computing environment has been used to validate our methodology.

In the second step we derive a matrix multiplication algorithm which enables us to obtain OUSAs with data pipeline period λ="3.

The practical realisation of this methodology is evidenced by a case studying the matrix multiplication algorithm as it is relatively simple and well known.

In February 2015, Maxeler published a dataflow implementation of the dense matrix multiplication algorithm, by splitting vector vector multiplications on DFEs, in order to increase the performance (application icon is given in Fig. 16).

This scheme only requires input of two external data in each step to maintain full operation of 4 PEs as highlighted in red circles in Figure 8. Figure 7 Illustration of subblock matrix multiplication algorithm and mapping onto SmartCell.

However, the use of these matrices for real-world applications is limited for several reasons: no fast matrix multiplication algorithm is available, huge memory requirements for large scale problems, difficult implementation on hardware, etc.

As examples, fast parallel matrix multiplication algorithms are discussed to illustrate the applicability of approach.

Dense matrix multiplication is a core component of many high-performance computing and machine learning algorithms, but the performance of matrix multiplication algorithms can vary significantly based on input parameters and hardware architecture.

On sorting and matrix multiplication algorithms, we also show that our approach scales up optimally with the number of basic hardware components.

The two versions are customized for matrix multiplication algorithms.

The approach is also efficient as sensing matrices with fast matrix multiplication algorithms can be used, in particular in the case of Fourier measurements.