Hugo 0.53, hugo-academic 3.3.0

This commit is contained in:
Carl Pearson
2019-01-08 16:56:56 -06:00
parent 12ff460bd3
commit 985ec36c9d
15 changed files with 352 additions and 113 deletions

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@@ -9,12 +9,12 @@ authors = ["Xuhao Chen", "Shengzhao Wu", "Li-Wen Chang", "Wei-Sheng Huang", "Car
# Publication type.
# Legend:
# 0 = Uncategorized
# 1 = Conference proceedings
# 2 = Journal
# 3 = Work in progress
# 4 = Technical report
# 1 = Conference paper
# 2 = Journal article
# 3 = Manuscript
# 4 = Report
# 5 = Book
# 6 = Book chapter
# 6 = Book section
publication_types = ["1"]
# Publication name and optional abbreviated version.
@@ -25,8 +25,28 @@ publication_short = ""
abstract = "Many-core accelerators, e.g. GPUs, are widely used for accelerating general-purpose compute kernels. With the SIMT execution model, GPUs can hide memory latency through massive multithreading for many regular applications. To support more applications with irregular memory access pattern, cache hierarchy is introduced to GPU architecture to capture input data sharing and mitigate the effect of irregular accesses. However, GPU caches suffer from poor efficiency due to severe contention, which makes it difficult to adopt heuristic management policies, and also limits system performance and energy-efficiency. We propose an adaptive cache management policy specifically for many-core accelerators. The tag array of L2 cache is enhanced with extra bits to track memory access history, an thus the locality information is captured and provided to L1 cache as heuristics to guide its run-time bypass and insertion decisions. By preventing un-reused data from polluting the cache and alleviating contention, cache efficiency is significantly improved. As a result, the system performance is improved by 31% on average for cache sensitive benchmarks, compared to the baseline GPU architecture."
abstract_short = ""
# Does this page contain LaTeX math? (true/false)
math = false
# Is this a selected publication? (true/false)
selected = false
# Projects (optional).
# Associate this publication with one or more of your projects.
# Simply enter your project's folder or file name without extension.
# E.g. `projects = ["deep-learning"]` references
# `content/project/deep-learning/index.md`.
# Otherwise, set `projects = []`.
projects = []
# Slides (optional).
# Associate this publication with Markdown slides.
# Simply enter your slide deck's filename without extension.
# E.g. `slides = "example-slides"` references
# `content/slides/example-slides.md`.
# Otherwise, set `slides = ""`.
slides = ""
# Tags (optional).
# Set `tags = []` for no tags, or use the form `tags = ["A Tag", "Another Tag"]` for one or more tags.
tags = []
# Does this page require source code highlighting? (true/false)
highlight = true
@@ -34,9 +54,6 @@ highlight = true
# Featured image thumbnail (optional)
image_preview = ""
# Is this a selected publication? (true/false)
selected = false
# Links (optional)
url_pdf = "pdf/2014chen.pdf"
url_preprint = ""
@@ -48,10 +65,24 @@ url_video = ""
url_poster = ""
url_source = ""
# Custom links (optional).
# Uncomment line below to enable. For multiple links, use the form `[{...}, {...}, {...}]`.
# url_custom = [{name = "Custom Link", url = "http://example.org"}]
# Digital Object Identifier (DOI)
doi = ""
# Does this page contain LaTeX math? (true/false)
math = false
# Featured image
# Place your image in the `static/img/` folder and reference its filename below, e.g. `image = "example.jpg"`.
[header]
image = ""
caption = ""
# To use, add an image named `featured.jpg/png` to your page's folder.
[image]
# Caption (optional)
caption = ""
# Focal point (optional)
# Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight
focal_point = ""
+++