Results 151 to 160 of about 2,725,619 (370)

Design of Linear Systolic Arrays for Matrix Multiplication

Advances in Electrical and Computer Engineering, 2014
This paper presents architecture for matrix multiplication optimized to be integrated as an accelerator unit to a host computer. Two linear systolic arrays with unidirectional data flow (ULSA), used as hardware accelerators, where synthesized in this ...
MILOVANOVIC, E. I., STOJCEV, M. K., MILOVANOVIC, I. Z., NIKOLIC, T. R.   +3 more
doaj   +1 more source

Advancing Research on Biomaterials and Biological Materials with Scanning Electron Microscopy under Environmental and Low Vacuum Conditions

Advanced Engineering Materials, EarlyView.
Herein, environmental scanning electron microscopy (ESEM) is discussed as a powerful extension of conventional SEM for life sciences. By combining high‐resolution imaging with variable pressure and humidity, ESEM allows the analysis of untreated biological materials, supports in situ monitoring of hydration‐driven changes, and advances the functional ...
Jendrian Riedel, Lea Dierker, Antoine Eyram Kwame, Kim Nora Wagner, Jonas J. Unterholzner, Jan‐Henning Dirks, Dorothea Brüggemann   +6 more
wiley   +1 more source

Application Level Synthesis: Creating Matrix-Matrix Multiplication Library: A Case Study

IEEE Access
Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the lack of good algorithmic libraries.
Dhilleswararao Pudi, Yu Yang, Dimitrios Stathis, Sunil Kumar Prajapati, Srinivas Boppu, Ahmed Hemani, Linga Reddy Cenkeramaddi   +6 more
doaj   +1 more source

Analog nanophotonic computing going practical: silicon photonic deep learning engines for tiled optical matrix multiplication with dynamic precision. [PDF]

Nanophotonics, 2023
Giamougiannis G, Tsakyridis A, Moralis-Pegios M, Pappas C, Kirtas M, Passalis N, Lazovsky D, Tefas A, Pleros N.   +8 more
europepmc   +1 more source

Microstructural Evolution and Mechanical Performance of Plasma‐Assisted Hybrid Friction Stir Welded Dissimilar Aluminum–Copper Joints

Advanced Engineering Materials, EarlyView.
Plasma‐assisted hybrid friction stir welding of dissimilar AlCu joints employs localized plasma preheating to balance heat input and enhance plastic flow. The optimized process reduces axial force by up to 35%, refines the microstructure, and achieves ≈96% joint efficiency.
Deepak Kumar Yaduwanshi, Pankaj Shrivastava, Ganesh Chouhan, Velaphi Msomi   +3 more
wiley   +1 more source

Performance Aspects of Sparse Matrix-Vector Multiplication

Acta Polytechnica, 2006
Sparse matrix-vector multiplication (shortly SpM×V) is an important building block in algorithms solving sparse systems of linear equations, e.g., FEM.
I. Šimeček
doaj  

Very large-scale diffraction investigations enabled by a matrix-multiplication facilitated radial and azimuthal integration algorithm: MatFRAIA. [PDF]

J Synchrotron Radiat, 2022
Jensen AB, Christensen TEK, Weninger C, Birkedal H.   +3 more
europepmc   +1 more source

Flexible Distributed Matrix Multiplication [PDF]

, 2022
Weiqi Li, Zhen Chen, Zhiying Wang, Syed A. Jafar, Hamid Jafarkhani   +4 more
openalex   +1 more source

Can Ti‐Based MXenes Serve as Solid Lubricants for Brake Applications? A Tribological Study

Advanced Engineering Materials, EarlyView.
This study explores the first implementation of Ti‐based MXenes materials in brake pad friction composite material. The resulting composite material exhibits a 48% reduction in the wear rate; alongside significant improvements are observed for thermal and mechanical properties.
Eslam Mahmoud, Jakob Gruber, Hakan Göçerler, Pierluigi Bilotto, Christian Gierl‐Mayer, Elham Loni, Michael Naguib, Carsten Gachot   +7 more
wiley   +1 more source

SpDRAM: Efficient In-DRAM Acceleration of Sparse Matrix-Vector Multiplication

IEEE Access
We introduce novel sparsity-aware in-DRAM matrix mapping techniques and a corresponding DRAM-based acceleration framework, termed SpDRAM, which utilizes a triple row activation scheme to efficiently handle sparse matrix-vector multiplication (SpMV).
Jieui Kang, Soeun Choi, Eunjin Lee, Jaehyeong Sim   +3 more
doaj   +1 more source