diff --git a/assets/scss/custom.scss b/assets/scss/custom.scss index e90e37b4..b7791fb5 100644 --- a/assets/scss/custom.scss +++ b/assets/scss/custom.scss @@ -79,6 +79,30 @@ h6 { font-size: 1rem; } +.h1 { + @extend h1; +} + +.h2 { + @extend h2; +} + +.h3 { + @extend h3; +} + +.h4 { + @extend h4; +} + +.h5 { + @extend h5; +} + +.h6 { + @extend h6; +} + .search-header { z-index: 1032; } @@ -165,9 +189,10 @@ html { transition-property: background-color; } +.tag-cloud a:active, .tag-cloud a:hover, .tag-cloud a:focus { - background-color: rgba(0, 0, 0, .2); + background-color: rgba(0, 0, 0, .1); transform: scale(1); } diff --git a/content/landing/_index.md b/content/landing/_index.md index 47ff9b43..54e96d42 100644 --- a/content/landing/_index.md +++ b/content/landing/_index.md @@ -2,14 +2,15 @@ title = "Topics" subtitle = "" +++ +
-## [Tutorials](/tutorials) are perfect for introducing yourself to a new topic. +[Tutorials](/tutorials) are perfect for introducing yourself to a new topic. Some tutorials are offered as in-person and/or Zoom workshops regularly. Find the notes or slides and download materials [on the Tutorials page](/tutorials). For a list of upcoming tutorials, please see [the Workshops page](https://www.rc.virginia.edu/education/workshops/) at the UVARC Website. -## [Programming courses](/courses) are longer and more in-depth than tutorials or workshops and teach more fundamental programming topics. +[Programming courses](/courses) are longer and more in-depth than tutorials or workshops and teach more fundamental programming topics.
diff --git a/content/notes/pytorch-hpc/gpu.md b/content/notes/pytorch-hpc/gpu.md index dcc98248..1aa90fd7 100644 --- a/content/notes/pytorch-hpc/gpu.md +++ b/content/notes/pytorch-hpc/gpu.md @@ -22,7 +22,7 @@ Neural Networks can grow large and contain many million if not billions of param - **High memory bandwidth** for efficient data transfer - Optimized for **tensor operations** (e.g., matrix multiplications) -If you’re working with a small model or smaller dataset, you may find using a GPU slows down your work.This is mainly due to the overhead cost of transfering data back and forward to the CPU. To find out if your task could benefit from using GPUs, it’s important to benchmark and profile your code. Learn more about Benchmarking and Profiling here: https://learning.rc.virginia.edu/notes/benchmark-parallel-programs/ https://learning.rc.virginia.edu/courses/python-high-performance/ +If you’re working with a small model or smaller dataset, you may find using a GPU slows down your work.This is mainly due to the overhead cost of transfering data back and forward to the CPU. To find out if your task could benefit from using GPUs, it’s important to benchmark and profile your code. Learn more about [Benchmarking and Profiling](https://learning.rc.virginia.edu/notes/benchmark-parallel-programs/) and [High-Performance Python](https://learning.rc.virginia.edu/courses/python-high-performance/). --- @@ -95,6 +95,6 @@ sstat job_id Alternatively you can use the [SLURM Script Generator](https://www.rc.virginia.edu/userinfo/hpc/slurm-script-generator/) to create your script. -For more information on SLURM visit: https://www.rc.virginia.edu/userinfo/hpc/software/pytorch/, https://www.rc.virginia.edu/userinfo/hpc/slurm/ +For more information on SLURM, visit [PyTorch on UVA HPC](https://www.rc.virginia.edu/userinfo/hpc/software/pytorch/) and [SLURM at UVA Research Computing](https://www.rc.virginia.edu/userinfo/hpc/slurm/). -For information on multi-GPU use: https://pytorch.org/tutorials/beginner/ddp_series_multigpu.html +For information on multi-GPU use, see the [PyTorch multi-GPU tutorial](https://pytorch.org/tutorials/beginner/ddp_series_multigpu.html). diff --git a/content/notes/pytorch-hpc/overview.md b/content/notes/pytorch-hpc/overview.md index 970c4f03..c6f3634e 100644 --- a/content/notes/pytorch-hpc/overview.md +++ b/content/notes/pytorch-hpc/overview.md @@ -96,18 +96,18 @@ Activation functions introduce non-linearity into neural networks, enabling them
- {{< figure src="/courses/pytorch-hpc/img/sigmoid.png" caption="Sigmoid" alt="Line graph of the Sigmoid activation function showing an S-shaped curve with output ranging from 0 to 1" width="400px" >}} + {{< figure src="/notes/pytorch-hpc/img/sigmoid.png" caption="Sigmoid" alt="Line graph of the Sigmoid activation function showing an S-shaped curve with output ranging from 0 to 1" width="400px" >}}
- {{< figure src="/courses/pytorch-hpc/img/tanh.png" caption="Tanh" alt="Line graph of the Tanh activation function showing an S-shaped curve with output ranging from -1 to 1" width="400px" >}} + {{< figure src="/notes/pytorch-hpc/img/tanh.png" caption="Tanh" alt="Line graph of the Tanh activation function showing an S-shaped curve with output ranging from -1 to 1" width="400px" >}}
- {{< figure src="/courses/pytorch-hpc/img/relu.png" caption="ReLU" alt="Line graph of the ReLU activation function showing zero output for negative inputs and a linear increase for positive inputs" width="400px" >}} + {{< figure src="/notes/pytorch-hpc/img/relu.png" caption="ReLU" alt="Line graph of the ReLU activation function showing zero output for negative inputs and a linear increase for positive inputs" width="400px" >}}
- {{< figure src="/courses/pytorch-hpc/img/leakyrelu.png" caption="Leaky ReLU" alt="Line graph of the Leaky ReLU activation function showing a small negative slope for negative inputs and a linear increase for positive inputs" width="400px" >}} + {{< figure src="/notes/pytorch-hpc/img/leakyrelu.png" caption="Leaky ReLU" alt="Line graph of the Leaky ReLU activation function showing a small negative slope for negative inputs and a linear increase for positive inputs" width="400px" >}}
diff --git a/content/notes/pytorch-hpc/project.md b/content/notes/pytorch-hpc/project.md index 54f5c3b1..29481e57 100644 --- a/content/notes/pytorch-hpc/project.md +++ b/content/notes/pytorch-hpc/project.md @@ -35,7 +35,7 @@ pytorch_project/ Tracking experiments is essential for understanding model performance. Using TensorBoard for Monitoring -TensorBoard is Tensorflow's visualization toolkit. It is compatible with PyTorch and enbles you to keep track of your experiments' metrics like lossand accuracy and easily visualize them. For more information visit: https://www.tensorflow.org/tensorboard +TensorBoard is Tensorflow's visualization toolkit. It is compatible with PyTorch and enbles you to keep track of your experiments' metrics like lossand accuracy and easily visualize them. For more information, visit the [TensorBoard documentation](https://www.tensorflow.org/tensorboard). ```python from torch.utils.tensorboard import SummaryWriter diff --git a/content/tutorials/dl-drug-discovery/index.md b/content/tutorials/dl-drug-discovery/index.md index f9561be0..a1e4d48c 100644 --- a/content/tutorials/dl-drug-discovery/index.md +++ b/content/tutorials/dl-drug-discovery/index.md @@ -2,7 +2,7 @@ title: "Deep Learning in Drug Discovery" date: "2025-05-14T00:00:00" authors: [ppr] -categories: [Deep learning"] +categories: ["Deep Learning"] tags: ["Deep_learning"] summary: "This tutorial introduces the deep learning approach to computational drug discovery." diff --git a/layouts/shortcodes/categories.html b/layouts/shortcodes/categories.html index b6baa7c4..2dc45600 100644 --- a/layouts/shortcodes/categories.html +++ b/layouts/shortcodes/categories.html @@ -42,8 +42,8 @@ {{ $fontStep := div $fontDelta $delta }}
-
- +
+ Categories: {{ if ne (upper .Page.Title) "ARCHIVED" }} - - {{ replaceRE `([^\\])_` "$1 " .Page.Title | upper }} - ({{ $tagCount }}) - + {{- $processedTitle := replaceRE `([^\\])_` "$1 " .Page.Title -}} + + {{ $processedTitle | upper }} + ({{ $tagCount }}) + {{ end }} {{ end }}