All results of finished domains can be retrieved while other domains are still in computation of pending. The status of the computations may be tracked via hexdumps of the status file. Things, that are improved or enhanced: Restart is now working. Depending on the current position of the ranks during the computation, some domains may be lost. They have to be computed in a subsequent computation. An additional program crawls the final results and writes them to comma separated value files with tailored suffixes to retrieve the results. Only the main ranks of the worker communicators write the results of the whole domain to the file system while minimizing the number of files by using the PureDat format. The preallocation of the PETSc math ...
In this release an optimization was made so that safe calls to operations do not have to call the e...
140 pagesTensor algebra lives at the heart of big data applications. Where classical machine learnin...
Operations with scalars are now more deterministic. Thanks to @wzzhu and @bezineb5 for contributing ...
All results of finished domains can be retrieved while other domains are still in computation of pen...
The DTC process chain now is tightly integrated with power and memory logging on HLRS Hawk. Both met...
Tensors are higher-dimensional analogs of matrices, and represent a key data abstraction for many ap...
This folder contains data files and code to reproduce the work done for paper Computation predicts r...
Memristor-based, non-von-Neumann architectures performing tensor operations directly in memory are a...
v0.9.6 saw some updates to the Repeat operation. This release fixes some performance hits that the R...
C3D file format is widely used in the biomechanical field by companies and laboratories to store mot...
Complete performance measurements data for the article "Assessment of Python Tensor Contraction Pack...
Major Changes Removes the various compute_* methods from Surface and Curve classes in favor of a un...
In this release, we continued working on the performance of some algorithms and modules. The reconst...
Deep Learning (DL) has created a growing demand for simpler ways to develop complex models and effic...
This dissertation is concerned with the development of novel high-performance algorithms for tensor ...
In this release an optimization was made so that safe calls to operations do not have to call the e...
140 pagesTensor algebra lives at the heart of big data applications. Where classical machine learnin...
Operations with scalars are now more deterministic. Thanks to @wzzhu and @bezineb5 for contributing ...
All results of finished domains can be retrieved while other domains are still in computation of pen...
The DTC process chain now is tightly integrated with power and memory logging on HLRS Hawk. Both met...
Tensors are higher-dimensional analogs of matrices, and represent a key data abstraction for many ap...
This folder contains data files and code to reproduce the work done for paper Computation predicts r...
Memristor-based, non-von-Neumann architectures performing tensor operations directly in memory are a...
v0.9.6 saw some updates to the Repeat operation. This release fixes some performance hits that the R...
C3D file format is widely used in the biomechanical field by companies and laboratories to store mot...
Complete performance measurements data for the article "Assessment of Python Tensor Contraction Pack...
Major Changes Removes the various compute_* methods from Surface and Curve classes in favor of a un...
In this release, we continued working on the performance of some algorithms and modules. The reconst...
Deep Learning (DL) has created a growing demand for simpler ways to develop complex models and effic...
This dissertation is concerned with the development of novel high-performance algorithms for tensor ...
In this release an optimization was made so that safe calls to operations do not have to call the e...
140 pagesTensor algebra lives at the heart of big data applications. Where classical machine learnin...
Operations with scalars are now more deterministic. Thanks to @wzzhu and @bezineb5 for contributing ...