Results 291 to 300 of about 652,834 (343)

MatRaptor: A Sparse-Sparse Matrix Multiplication Accelerator Based on Row-Wise Product

Micro, 2020
Sparse-sparse matrix multiplication (SpGEMM) is a computation kernel widely used in numerous application domains such as data analytics, graph processing, and scientific computing.
Nitish Srivastava, Hanchen Jin, Jie Liu, D. Albonesi, Zhiru Zhang   +4 more
semanticscholar   +1 more source

Accelerating Learning About Accelerators

2018
This book presents a range of observations about impact-oriented accelerators and the entrepreneurs and ventures that they attract and sometimes work with. Relying on data collected through the many programs that partnered with the EDP from 2013 to 2017, these observations provide consistent evidence that accelerators are influencing short-term ...
Peter W. Roberts, Saurabh A. Lall
openaire   +1 more source

Ambit: In-Memory Accelerator for Bulk Bitwise Operations Using Commodity DRAM Technology

Micro, 2017
Many important applications trigger bulk bitwise operations, i.e., bitwise operations on large bit vectors. In fact, recent works design techniques that exploit fast bulk bitwise operations to accelerate databases (bitmap indices, BitWeaving) and web ...
Vivek Seshadri, Donghyuk Lee, Thomas Mullins, Hasan Hassan, Amirali Boroumand, Jeremie S. Kim, M. Kozuch, O. Mutlu, Phillip B. Gibbons, T. Mowry   +9 more
semanticscholar   +1 more source

Can Accelerators Accelerate Learning?

AIP Conference Proceedings, 2009
The ‘Young Talented’ education program developed by the Brazilian State Funding Agency (FAPERJ) [1] makes it possible for high‐schools students from public high schools to perform activities in scientific laboratories. In the Atomic and Molecular Physics Laboratory at Federal University of Rio de Janeiro (UFRJ), the students are confronted with modern ...
A. C. F. Santos, P. Fonseca, L. F. S. Coelho, Floyd D. McDaniel, Barney L. Doyle   +4 more
openaire   +1 more source

Acceleration Principle

1987
The acceleration principle holds that the demand for capital goods is a derived demand and that changes in the demand for output lead to changes in the demand for capital stock and, hence, lead to investment. The flexible accelerator, which includes both demand and supply elements, allows for lags in the adjustment of the actual capital stock towards ...
Junankar, Pramod N., Durlauf, Steven N., Blume, Lawrence E.   +2 more
openaire   +2 more sources

ExTensor: An Accelerator for Sparse Tensor Algebra

Micro, 2019
Generalized tensor algebra is a prime candidate for acceleration via customized ASICs. Modern tensors feature a wide range of data sparsity, with the density of non-zero elements ranging from 10-6% to 50%.
Kartik Hegde, Hadi Asghari Moghaddam, Michael Pellauer, N. Crago, A. Jaleel, Edgar Solomonik, J. Emer, Christopher W. Fletcher   +7 more
semanticscholar   +1 more source

Accelerated entropy estimates with accelerated dynamics

The Journal of Chemical Physics, 2007
Accelerated dynamics is applied to entropy calculations on a set of toy and molecular systems and is found to enhance the rate of convergence.
David D L, Minh, Donald, Hamelberg, J Andrew, McCammon   +2 more
openaire   +2 more sources

SparTen: A Sparse Tensor Accelerator for Convolutional Neural Networks

Micro, 2019
Convolutional neural networks (CNNs) are emerging as powerful tools for image processing. Recent machine learning work has reduced CNNs' compute and data volumes by exploiting the naturally-occurring and actively-transformed zeros in the feature maps and
Ashish Gondimalla, Noah Chesnut, Mithuna Thottethodi, T. N. Vijaykumar   +3 more
semanticscholar   +1 more source

Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks

IEEE Journal of Solid-State Circuits, 2016
Yu-hsin Chen, T. Krishna, J. Emer, V. Sze   +3 more
semanticscholar   +1 more source

Accelerated hypofractionation

International Journal of Radiation Oncology*Biology*Physics, 2005
Minesh, Mehta, Jack, Fowler
openaire   +2 more sources