Merge branch 'master' of github.com:cwpearson/hugo-cwpearson
This commit is contained in:
@@ -270,7 +270,7 @@ enableGitInfo = false
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[[params.social]]
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icon = "google-scholar"
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icon_pack = "ai"
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link = "https://scholar.google.co.uk/citations?user=K2nzqpYAAAAJ"
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link = "https://scholar.google.com/citations?user=K2nzqpYAAAAJ"
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[[params.social]]
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icon = "github"
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@@ -13,11 +13,15 @@ widget = "custom"
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weight = 50
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+++
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Dan Vivoli Endowed Fellowship - UIUC 2018-2019
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Best Paper and ACM Artifact Evaluation Stamp for [Evaluating CUDA Communication Primitives on High-Bandwidth Interconnects](/publication/20190410_pearson_icpe) - ICPE 2019
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[E. A. Reid Fellowship](https://ece.illinois.edu/academics/grad/fellowships/reid) - UIUC 2019-2020
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[Dan Vivoli Endowed Fellowship](https://ece.illinois.edu/academics/grad/fellowships/vivoli) - UIUC 2018-2019
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[MIT Graph Challenge](https://graphchallenge.mit.edu/champions) Finalist - UIUC 2018
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Mavis Future Faculty Fellowship - UIUC 2017-2018
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[Mavis Future Faculty Fellowship](http://publish.illinois.edu/engr-mavis/) - UIUC 2017-2018
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Top-20 Poster - NVIDIA GPU Technology Conference 2017
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@@ -28,10 +28,10 @@ summary = "Paper accepted at ICPE 2019"
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# Focal point (optional)
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# Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight
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focal_point = ""
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focal_point = "Center"
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# Show image only in page previews?
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preview_only = false
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preview_only = true
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categories = []
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@@ -2,7 +2,7 @@
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title = "Bio Snippet"
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subtitle = ""
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date = 2019-03-13T00:00:00
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lastmod = 2019-03-13T00:00:00
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lastmod = 2019-03-26T00:00:00
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draft = false
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# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.
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@@ -28,16 +28,19 @@ summary = "A short biography of Carl Pearson for general use"
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# Focal point (optional)
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# Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight
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focal_point = "Smart"
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focal_point = "Top"
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# Show image only in page previews?
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preview_only = false
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preview_only = true
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categories = []
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+++
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Carl Pearson is a PhD candidate in the Electrical Computer and Engineering Department at the University of Illinois Urbana-Champaign.
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He is a member of the [IMPACT Research Group](http://impact.crhc.illinois.edu/) and advised by Professor Wen-Mei Hwu.
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His current research focus is on multi-GPU graph algorithms, and more broadly he is interested in high performance computing, GPU computing, compilers, and high-level programming languages and frameworks.
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He was awarded the 2017-2018 Dan Vivoli GPU computing fellowship from the University of Illinois Urbana-Champaign.
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Carl Pearson is currently a PhD candidate in the Electrical Computer and Engineering Department at the University of Illinois Urbana-Champaign.
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He is a member of the [IMPACT Research Group](http://impact.crhc.illinois.edu/) and advised by Professor Wen-Mei Hwu where he works on high performance computing, GPU computing, compilers, and high-level programming languages and frameworks, with an emphasis on multi-GPU graph algorithms.
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He also enjoys teaching and mentoring undergraduate and graduate students in GPU programming courses.
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<img src="/img/headshot.jpg" alt="drawing" width="200"/>
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*For full size, right-click and view image.*
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45
content/post/20190326-reid/index.md
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content/post/20190326-reid/index.md
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+++
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title = "Received E.A. Reid Fellowship"
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subtitle = ""
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date = 2019-03-26T00:00:00
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lastmod = 2019-03-26T00:00:00
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draft = false
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# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.
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authors = ["Carl Pearson"]
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tags = []
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summary = "Received the UIUC ECE Department's E. A. Reid Fellowship"
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# Projects (optional).
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# Associate this post with one or more of your projects.
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||||
# Simply enter your project's folder or file name without extension.
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||||
# E.g. `projects = ["deep-learning"]` references
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# `content/project/deep-learning/index.md`.
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# Otherwise, set `projects = []`.
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# projects = ["internal-project"]
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# Featured image
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# To use, add an image named `featured.jpg/png` to your project's folder.
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[image]
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# Caption (optional)
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caption = "Carl Pearson"
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# Focal point (optional)
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# Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight
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focal_point = "Smart"
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# Show image only in page previews?
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preview_only = false
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categories = []
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+++
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I have received the [Ernest A. Reid Fellowship in Electrical Engineering](https://ece.illinois.edu/academics/grad/fellowships/reid) for the 2019-2020 academic year!
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This fellowship is given to a student or students with exceptional promise for an academic career; particularly demonstrating interest in and capability for the instructional program. The objective of the fellowship is to encourage students to consider an academic career.
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My gratitude to the selection committee, and to Mrs. Nell W. Reid for establishing the fellowship in honor of her husband.
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BIN
content/post/20190411-icpe-best-paper/featured.png
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content/post/20190411-icpe-best-paper/featured.png
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content/post/20190411-icpe-best-paper/index.md
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content/post/20190411-icpe-best-paper/index.md
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+++
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title = "Best Paper award at ICPE!"
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subtitle = ""
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date = 2019-04-11T00:00:00
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lastmod = 2019-04-11T00:00:00
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draft = false
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# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.
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authors = ["Carl Pearson"]
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tags = []
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summary = "Best research track paper at ICPE"
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# Projects (optional).
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||||
# Associate this post with one or more of your projects.
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||||
# Simply enter your project's folder or file name without extension.
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||||
# E.g. `projects = ["deep-learning"]` references
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||||
# `content/project/deep-learning/index.md`.
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# Otherwise, set `projects = []`.
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# projects = ["internal-project"]
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# Featured image
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# To use, add an image named `featured.jpg/png` to your project's folder.
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[image]
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# Caption (optional)
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caption = "Image credit: [**ICPE**](https://icpe2019.spec.org/)"
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# Focal point (optional)
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# Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight
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focal_point = "Center"
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# Show image only in page previews?
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preview_only = true
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categories = []
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+++
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My paper *Evaluating Characteristics of CUDA Communication Primitives on High-Bandwidth Interconnects* won the best paper award at ICPE!
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@@ -35,7 +35,7 @@ highlight = false
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image_preview = ""
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# Is this a selected publication? (true/false)
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selected = true
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||||
selected = false
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||||
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||||
# Projects (optional).
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||||
# Associate this publication with one or more of your projects.
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||||
|
82
content/publication/20190410_pearson_icpe/index.md
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82
content/publication/20190410_pearson_icpe/index.md
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@@ -0,0 +1,82 @@
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+++
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title = "Evaluating Characteristics of CUDA Communication Primitives on High-Bandwidth Interconnects"
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date = 2019-04-09T00:00:00 # Schedule page publish date.
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draft = false
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# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.
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authors = ["Carl Pearson", "Adbul Dakkak", "Sarah Hashash", "Cheng Li", "I-Hsin Chung", "Jinjun Xiong", "Wen-Mei Hwu"]
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# Publication type.
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# Legend:
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# 0 = Uncategorized
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# 1 = Conference paper
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# 2 = Journal article
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# 3 = Manuscript
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# 4 = Report
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# 5 = Book
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# 6 = Book section
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publication_types = ["1"]
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# Publication name and optional abbreviated version.
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publication = "In *2019 ACM/SPEC International Conference on Performance Engineering*"
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publication_short = "In *ICPE*"
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# Abstract and optional shortened version.
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abstract = """Data-intensive applications such as machine learning and analytics have created a demand for faster interconnects to avert the memory bandwidth wall and allow GPUs to be effectively leveraged for lower compute intensity tasks. This has resulted in wide adoption of heterogeneous systems with varying underlying interconnects, and has delegated the task of understanding and copying data to the system or application developer. No longer is a malloc followed by memcpy the only or dominating modality of data transfer; application developers are faced with additional options such as unified memory and zero-copy memory. Data transfer performance on these systems is now impacted by many factors including data transfer modality, system interconnect hardware details, CPU caching state, CPU power management state, driver policies, virtual memory paging efficiency, and data placement.
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This paper presents Comm|Scope, a set of microbenchmarks designed for system and application developers to understand memory transfer behavior across different data placement and exchange scenarios.
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Comm|Scope comprehensively measures the latency and bandwidth of CUDA data transfer primitives, and avoids common pitfalls in ad-hoc measurements by controlling CPU caches, clock frequencies, and avoids measuring synchronization costs imposed by the measurement methodology where possible.
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This paper also presents an evaluation of Comm|Scope on systems featuring the POWER and x86 CPU architectures and PCIe 3, NVLink 1, and NVLink 2 interconnects.
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These systems are chosen as representative configurations of current high-performance GPU platforms.
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Comm|Scope measurements can serve to update insights about the relative performance of data transfer methods on current systems.
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This work also reports insights for how high-level system design choices affect the performance of these data transfers, and how developers can optimize applications on these systems."""
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abstract_short = "This paper presents Comm|Scope, a set of microbenchmarks designed for system and application developers to understand memory transfer behavior across different data placement and exchange scenarios."
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# Does this page contain LaTeX math? (true/false)
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math = false
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# Does this page require source code highlighting? (true/false)
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highlight = false
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# Featured image thumbnail (optional)
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image_preview = ""
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# Is this a selected publication? (true/false)
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selected = true
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||||
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||||
# Projects (optional).
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# Associate this publication with one or more of your projects.
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||||
# Simply enter your project's folder or file name without extension.
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||||
# E.g. `projects = ["deep-learning"]` references
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# `content/project/deep-learning/index.md`.
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# Otherwise, set `projects = []`.
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projects = ["scope"]
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# Links (optional)
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url_pdf = "pdf/20190410_pearson_icpe.pdf"
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url_preprint = ""
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url_code = "https://github.com/c3sr/comm_scope"
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url_dataset = ""
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url_project = ""
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url_slides = "/pdf/20190410_pearson_icpe_slides.pdf"
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url_video = ""
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url_poster = ""
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url_source = ""
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# Featured image
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# To use, add an image named `featured.jpg/png` to your page's folder.
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[image]
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# Caption (optional)
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caption = ""
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||||
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# Focal point (optional)
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# Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight
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focal_point = ""
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+++
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* Best Paper for the ICPE research track papers
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* Functional ACM Artifact Evaluation.
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<img src="/img/acm_artifact_functional.jpg" alt="functional artifact" width="200"/>
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92
content/talk/20190410icpe/index.md
Normal file
92
content/talk/20190410icpe/index.md
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@@ -0,0 +1,92 @@
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+++
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title = "Evaluating Characteristics of CUDA Communication Primitives on High-Bandwidth Interconnects"
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date = 2019-03-26T00:00:00 # Schedule page publish date.
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draft = false
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# Talk start and end times.
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# End time can optionally be hidden by prefixing the line with `#`.
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time_start = 2019-04-10T16:00:00
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time_end = 2019-04-10T17:50:00
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# Authors. Comma separated list, e.g. `["Bob Smith", "David Jones"]`.
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authors = ["Carl Pearson"]
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# Abstract and optional shortened version.
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abstract = """Data-intensive applications such as machine learning and analytics have created a demand for faster interconnects to avert the memory bandwidth wall and allow GPUs to be effectively leveraged for lower compute intensity tasks. This has resulted in wide adoption of heterogeneous systems with varying underlying interconnects, and has delegated the task of understanding and copying data to the system or application developer. No longer is a malloc followed by memcpy the only or dominating modality of data transfer; application developers are faced with additional options such as unified memory and zero-copy memory. Data transfer performance on these systems is now impacted by many factors including data transfer modality, system interconnect hardware details, CPU caching state, CPU power management state, driver policies, virtual memory paging efficiency, and data placement.
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||||
|
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This paper presents Comm|Scope, a set of microbenchmarks designed for system and application developers to understand memory transfer behavior across different data placement and exchange scenarios.
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Comm|Scope comprehensively measures the latency and bandwidth of CUDA data transfer primitives, and avoids common pitfalls in ad-hoc measurements by controlling CPU caches, clock frequencies, and avoids measuring synchronization costs imposed by the measurement methodology where possible.
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||||
This paper also presents an evaluation of Comm|Scope on systems featuring the POWER and x86 CPU architectures and PCIe 3, NVLink 1, and NVLink 2 interconnects.
|
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These systems are chosen as representative configurations of current high-performance GPU platforms.
|
||||
Comm|Scope measurements can serve to update insights about the relative performance of data transfer methods on current systems.
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This work also reports insights for how high-level system design choices affect the performance of these data transfers, and how developers can optimize applications on these systems."""
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abstract_short = "This paper presents Comm|Scope, a set of microbenchmarks designed for system and application developers to understand memory transfer behavior across different data placement and exchange scenarios."
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# Name of event and optional event URL.
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event = "ACM/SPEC International Conference on Performance Engineering"
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event_url = "https://icpe2019.spec.org/"
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# Location of event.
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location = "Mumbai, India"
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# Is this a selected talk? (true/false)
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selected = true
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||||
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# Projects (optional).
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# Associate this talk with one or more of your projects.
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||||
# Simply enter your project's folder or file name without extension.
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||||
# E.g. `projects = ["deep-learning"]` references
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# `content/project/deep-learning/index.md`.
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# Otherwise, set `projects = []`.
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projects = ["scope"]
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# Tags (optional).
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# Set `tags = []` for no tags, or use the form `tags = ["A Tag", "Another Tag"]` for one or more tags.
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||||
tags = []
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||||
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# Slides (optional).
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# Associate this talk with Markdown slides.
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# Simply enter your slide deck's filename without extension.
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# E.g. `slides = "example-slides"` references
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# `content/slides/example-slides.md`.
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# Otherwise, set `slides = ""`.
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slides = ""
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# Links (optional).
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url_pdf = ""
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url_slides = "/pdf/20190410_pearson_icpe_slides.pdf"
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url_video = ""
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url_code = ""
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# Does the content use math formatting?
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math = false
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# Featured image
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||||
# To use, add an image named `featured.jpg/png` to your page's folder.
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[image]
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||||
# Caption (optional)
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||||
caption = ""
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||||
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# Focal point (optional)
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||||
# Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight
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focal_point = "Right"
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+++
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You can find the paper [here](/publication/20190410_pearson_icpe).
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Thanks to my co-authors:
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* Abdul Dakkak (University of Illinois Urbana-Champaign)
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* Sarah Hashash (University of Illinois Urbana-Champaign)
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* Cheng Li (University of Illinois Urbana-Champaign)
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* I-Hsin Chung (IBM T.J. Watson Research)
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* Jinjun Xiong (IBM T.J. Watson Research)
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* Wen-Mei Hwu (University of Illinois Urbana-Champaign)
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and thanks for the support of:
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* IBM-ILLINOIS Center for Cognitive Computing Systems Research (C3SR) - a research collaboration as part of the IBM AI Horizon Network.
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* The Blue Waters sustained-petascale computing project, which is supported by the National Science Foundation award OCI-0725070 and the state of Illinois.
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Blue Waters is a joint effort of the University of Illinois at Urbana-Champaign and its National Center for Supercomputing Applications.
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[program]: https://icpe2019.spec.org/conference-program.html#session9
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Reference in New Issue
Block a user