cwpearson/hugo-cwpearson
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Update hugo, academic-theme

Browse Source
This commit is contained in:
Carl Pearson
2017-10-18 14:06:25 -05:00
parent f2f01d8e4c
commit 057a7ac31e
7 changed files with 209 additions and 32 deletions
Download Patch File Download Diff File Expand all files Collapse all files

52
content/publication/20170621_pearson_cem.md
View File

@@ -1,23 +1,57 @@
+++
title = "Comparative Performance Evaluation of Multi-GPU MLFMM Implementation for 2-D VIE Problems"
date = 2017-06-21
draft = false
date = "2017-06-21"
title = "Comparative Performance Evaluation of Multi-GPU MLFMM Implementation for 2-D VIE Problems"
# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.
authors = ["Carl Pearson", "Mert Hidayetoglu", "Wei Ren", "Weng Cho Chew", "Wen-Mei Hwu"]
abstract = 'We compare multi-GPU performance of the multilevel fast multipole method (MLFMM) on two different systems: A shared-memory IBM S822LC workstation with four NVIDIA P100 GPUs, and 16 XK nodes (each is employed with a single NVIDIA K20X GPU) of the Blue Waters supercomputer. MLFMM is implemented for solving scattering problems involving two-dimensional inhomogeneous bodies. Results show that the multi-GPU implementation provides 794 and 969 times speedups on the IBM and Blue Waters systems over their corresponding sequential CPU executions, respectively, where the sequential execution on the IBM system is 1.17 times faster than on the Blue Waters System.'
# Publication type.
# Legend:
# 0 = Uncategorized
# 1 = Conference proceedings
# 2 = Journal
# 3 = Work in progress
# 4 = Technical report
# 5 = Book
# 6 = Book chapter
publication_types = ["1"]
image = ""
image_preview = ""
# Publication name and optional abbreviated version.
publication = "Computing and Electromagnetics International Workshop, IEEE 2017"
publication_short = "CEM"
# Abstract and optional shortened version.
abstract = "We compare multi-GPU performance of the multilevel fast multipole method (MLFMM) on two different systems: A shared-memory IBM S822LC workstation with four NVIDIA P100 GPUs, and 16 XK nodes (each is employed with a single NVIDIA K20X GPU) of the Blue Waters supercomputer. MLFMM is implemented for solving scattering problems involving two-dimensional inhomogeneous bodies. Results show that the multi-GPU implementation provides 794 and 969 times speedups on the IBM and Blue Waters systems over their corresponding sequential CPU executions, respectively, where the sequential execution on the IBM system is 1.17 times faster than on the Blue Waters System."
abstract_short = ""
# Does this page contain LaTeX math? (true/false)
math = false
publication = "*Computing and Electromagnetics International Workshop.* IEEE, 2017."
# Does this page require source code highlighting? (true/false)
highlight = true
# Featured image thumbnail (optional)
image_preview = ""
# Is this a selected publication? (true/false)
selected = false
# Links (optional)
url_pdf = "pdf/20170621_pearson_cem.pdf"
url_preprint = ""
url_code = ""
url_dataset = ""
url_pdf = "pdf/20170621_pearson_cem.pdf"
url_project = ""
url_slides = ""
url_video = ""
url_poster = ""
url_source = ""
selected = true
+++
# Featured image
# Place your image in the `static/img/` folder and reference its filename below, e.g. `image = "example.jpg"`.
[header]
image = ""
caption = ""
+++