CPU AND GPU PERFORMANCE ANALYSIS ON 2D MATRIX OPERATION

2021 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Kwek Benny Kurniawan ◽  
YB Dwi Setianto
Keyword(s):  
Graphic Processing Unit ◽  
Computing Time ◽  
General Purpose ◽  
Parallel Processors ◽  
Processing Unit ◽  
Matrix Operation ◽  
Industry Standard ◽  
Programming Interfaces ◽  
Complete Matrix ◽  
Matrix Calculation

GPU or Graphic Processing Unit can be used on many platforms in general GPUs are used for rendering graphics but now GPUs are general purpose parallel processors with support for easily accessible programming interfaces and industry standard languages such as C, Python and Fortran. In this study, the authors will compare CPU and GPU for completing some matrix calculation. To compare between CPU and GPU, the authors have done some testing to observe the use of Processing Unit, memory and computing time to complete matrix calculations by changing matrix sizes and dimensions. The results of tests that have been done shows asynchronous GPU is faster than sequential. Furthermore, thread for GPU needs to be adjusted to achieve efficiency in GPU load.

Potential of General Purpose Graphic Processing Unit for Energy Management System

2012 ◽  
Vol 3 (2) ◽  
pp. 72-82
Author(s):  
Jean-Charles Tournier ◽  
Vaibhav Donde ◽  
Zhao Li ◽  
Martin Naef
Keyword(s):  
Energy Management ◽  
Management System ◽  
Graphic Processing Unit ◽  
General Purpose ◽  
Energy Management System ◽  
Processing Unit ◽  
Server Side ◽  
And Performance ◽  
Speedup Factor ◽  
Graphic Processing

This paper investigates the potential of General Purpose Graphic Processing Unit (GPGPU) for the server and HMI parts of Energy Management System (EMS). The HMI investigation focuses on the applicability and performance improvement of GPGPU for scattered data interpolation algorithms typically used to visually represent the overall state of a power network. The server side investigation focuses on fine grain parallelization of EMS applications by targeting the sparse linear solver. The different performance evaluations show the high potential of GPGPU for the HMI part with a speedup factor up to 100 at the cost of acceptable approximations, while the benefit on the server side varies from a speedup factor of up to 300 to 0 depending on the application.

3D FEM simulation of SAW resonators using hierarchical cascading technique and general purpose graphic processing unit

2019 ◽  
Vol 58 (SG) ◽  
pp. SGGC05 ◽  
Author(s):  
Xinyi Li ◽  
Jingfu Bao ◽  
Luyan Qiu ◽  
Naoto Matsuoka ◽  
Tatsuya Omori ◽  
...  
Keyword(s):  
Graphic Processing Unit ◽  
Fem Simulation ◽  
General Purpose ◽  
Processing Unit ◽  
3D Fem ◽  
Graphic Processing ◽  
Saw Resonators

Using Inter-Block Synchronization to Improve the Knapsack Problem on GPUs

2018 ◽  
Vol 10 (4) ◽  
pp. 83-98 ◽  
Author(s):  
Xue Sun ◽  
Chao-Chin Wu ◽  
Liang-Rui Chen ◽  
Jian-You Lin
Keyword(s):  
Dynamic Programming ◽  
Shared Memory ◽  
Performance Improvement ◽  
Graphics Processing Unit ◽  
General Purpose ◽  
Parallel Processors ◽  
Processing Unit ◽  
Compression Method ◽  
Popular Method ◽  
Graphics Processing

This article describes how as one of the hot parallel processors, the general-purpose graphics processing unit (GPU) has been widely adopted to accelerate various time-consuming algorithms. Dynamic programming (DP) optimization is a popular method to solve a particular class of complex problems. This article focuses on serial-monadic DP problems onto NVIDIA GPUs. As 0/1 knapsack is one of the most representational problems in this category and it often arises in many other fields of applications. The previous work proposed the compression method to reduce the amount of data transferred, but data in shared memory cannot be reused. This article demonstrates how to apply a more condensed data structure and the inter-block synchronization to efficiently map the serial-monadic DP onto GPUs. Computational experiments reveal that the best performance improvement of the approach is about 100% comparing with the previous work.

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