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diff --git a/preview-xalim-pass-args-guide/fellowships/index.html b/preview-xalim-pass-args-guide/fellowships/index.html
index 90c3b8d49..9805e34a7 100644
--- a/preview-xalim-pass-args-guide/fellowships/index.html
+++ b/preview-xalim-pass-args-guide/fellowships/index.html
@@ -232,14 +232,14 @@
Featured Fellow
-
+
-
+
@@ -248,23 +248,28 @@
Featured Fellow
- Wil Cram
+ Kristina Zhao
-
Mentor(s):
Greg Thain
+
Mentor(s):
Emma Turetsky and Ian Ross
-
Schedd performance analysis for human
+
Integrating PyTorch and Pelican
-
The condor_schedd is a single threaded program, and when it is overloaded,
-it is difficult for administrators to understand why. There are some
-statistics about what it is doing, but there is no clear way to present
-this information in a useful way to an administrator. Students working
-on this project would build visualizations of complex data, and work
-with end users and facilitators to tune output for real world human
-consumption.
+
PyTorch is one of the most popular machine learning frameworks.
+An important aspect of using it is the data engineering: how
+is input data fed into the model during training? Going from
+“tutorial scale” problems to cutting-edge research requires
+drastically different techniques around data handling.
+
+
For this project, we aim to better integrate Pelican
+into the PyTorch community, providing both technical
+mechanisms (implementing the fsspec interface for Pelican)
+and documentation by providing tutorials and recipes for
+scaling PyTorch-based training using a combination of HTCondor
+and Pelican.
- Shanan Peters, project lead for xDD, Dean L. Morgridge Professor of Geology, Department of Geoscience.
Shanan’s primary research thrust involves quantifying the spatial and temporal distribution of rocks in the Earth’s crust in order to constrain the long-term evolution of life and Earth’s surface environment. Compiling data from scientific publications is a key component of this work and Peters and his collaborators are developing machine reading systems deployed over the xDD digital library ad cyberinfrastructure hosted in the CHTC for this purpose.
+ Natalia de Leon, Professor of Agronomy, Department of Agronomy.
The goal of her research is to identify efficient mechanisms to better understand the genetic constitution of economically relevant traits and to improve plant breeding efficiency. Her research integrates genomic, phenomic, and environmental information to accelerate translational research for enhanced sustainable crop productivity.
-
+
-
Natalia de Leon
+
xDD project and Shanan Peters
- Natalia de Leon, Professor of Agronomy, Department of Agronomy.
The goal of her research is to identify efficient mechanisms to better understand the genetic constitution of economically relevant traits and to improve plant breeding efficiency. Her research integrates genomic, phenomic, and environmental information to accelerate translational research for enhanced sustainable crop productivity.
+ Shanan Peters, project lead for xDD, Dean L. Morgridge Professor of Geology, Department of Geoscience.
Shanan’s primary research thrust involves quantifying the spatial and temporal distribution of rocks in the Earth’s crust in order to constrain the long-term evolution of life and Earth’s surface environment. Compiling data from scientific publications is a key component of this work and Peters and his collaborators are developing machine reading systems deployed over the xDD digital library ad cyberinfrastructure hosted in the CHTC for this purpose.
-
+
@@ -356,76 +356,76 @@
-
Biomagnetic Resonance Data Bank
+
CMS LHC Compact Muon Solenoid
- The Biomagnetic Resonance Data Bank (BMRB) is headquarted within UW-Madison's National Magnetic Resonance Facility at Madison (NMRFAM) and uses the CHTC for research in connection with the Biological Magnetic Resonance Data Bank (BMRB).
-
+ The UW team participating in the Compact Muon Solenoid (CMS) experiment analyzes petabytes of data from proton-proton collisions in the Large Hadron Collider (LHC). We use the unprecedented energies of the LHC to study Higgs Boson signatures, Electroweak Physics, and the possibility of exotic particles beyond the Standard Model of Particle Physics. Important calculations are also performed to better tune the experiment's trigger system, which is responsible for making nanosecond-scale decisions about which collisions in the LHC should be recorded for further analysis.
-
+
-
CMS LHC Compact Muon Solenoid
+
Atlas Experiment
- The UW team participating in the Compact Muon Solenoid (CMS) experiment analyzes petabytes of data from proton-proton collisions in the Large Hadron Collider (LHC). We use the unprecedented energies of the LHC to study Higgs Boson signatures, Electroweak Physics, and the possibility of exotic particles beyond the Standard Model of Particle Physics. Important calculations are also performed to better tune the experiment's trigger system, which is responsible for making nanosecond-scale decisions about which collisions in the LHC should be recorded for further analysis.
+ Atlas Experiment
-
+
-
Atlas Experiment
+
Barry Van Veen
- Atlas Experiment
+ The bio-signal processing laboratory develops statistical signal processing methods for biomedical problems. We use CHTC for casual network modeling of brain electrical activity. We develop methods for identifying network models from noninvasive measures of electric/ magnetic fields at the scalp, or invasive measures of the electric fields at or in the cortex, such as electrocorticography. Model identification involves high throughput computing applied to large datasets consisting of hundreds of spatial channels each containing thousands of time samples.
-
+
-
Phil Townsend
+
Biomagnetic Resonance Data Bank
- Professor Phil Townsend of Forestry and Wildlife Ecology says Our research (NASA & USDA Forest Service funded) strives to understand the outbreak dynamic of major forest insect pests in North America through simulation modeling. As part of this effort, we map forest species and their abundance using multi-temporal Landsat satellite data. My colleagues have written an automatic variable selection routine in MATLAB to preselect the most important image variables to model and map forest species abundance. However, depending on the number of records and the initial variables, this process can take weeks to run. Hence, we seek resources to speed up this process.
+ The Biomagnetic Resonance Data Bank (BMRB) is headquarted within UW-Madison's National Magnetic Resonance Facility at Madison (NMRFAM) and uses the CHTC for research in connection with the Biological Magnetic Resonance Data Bank (BMRB).
+
-
+
-
Barry Van Veen
+
Phil Townsend
- The bio-signal processing laboratory develops statistical signal processing methods for biomedical problems. We use CHTC for casual network modeling of brain electrical activity. We develop methods for identifying network models from noninvasive measures of electric/ magnetic fields at the scalp, or invasive measures of the electric fields at or in the cortex, such as electrocorticography. Model identification involves high throughput computing applied to large datasets consisting of hundreds of spatial channels each containing thousands of time samples.
+ Professor Phil Townsend of Forestry and Wildlife Ecology says Our research (NASA & USDA Forest Service funded) strives to understand the outbreak dynamic of major forest insect pests in North America through simulation modeling. As part of this effort, we map forest species and their abundance using multi-temporal Landsat satellite data. My colleagues have written an automatic variable selection routine in MATLAB to preselect the most important image variables to model and map forest species abundance. However, depending on the number of records and the initial variables, this process can take weeks to run. Hence, we seek resources to speed up this process.
In your working directory on the access point, download gapminder-life-expectancy.csv data.
+
+
In your working directory on the access point, download gapminder-life-expectancy.csv data.
+
[user@ap2002]$ wget [insert link here]
@@ -382,7 +384,7 @@
Writing a submit
Create a submit file for the job called least_squares.sub.
-
# least_squares.sub - an example HTCondor submit file for passing arguments
+
# least_squares.sub - an example HTCondor submit file for passing arguments
# Custom variable can be specified
country = Brazil
@@ -442,7 +444,9 @@
Leveraging $(Process)/$(ProcID) a
In this exercise, we will use $(Process) to estimate the life expectancy within the years 2000-2009.
-
Create a new submit file, least_squares_process.sub.
+
+
Create a new submit file, least_squares_process.sub.
+
# least_squares_process.sub - an example HTCondor submit file for passing arguments
# with the $(Process) variable
@@ -476,18 +480,22 @@
Leveraging $(Process)/$(ProcID) a
Notice the differences between this submit script and the previous one:
At the bottom of the script, queue 10 tells HTCondor to run 10 instances of our calculation. Each calculation will be assigned a number $(Process), which will range from 0 to 9.
-
We want to estimate life expectancy between 2000 and 2009, so we set a custom variable processplus = $(Process) + 2000. This is a string, i.e. “0 + 2000”. This isn’t what we want! We convert it to a useful integer value in the next line: year = $INT(processplus,%d). Each calculation can now use the variable $(year), which will now range from 2000 to 2009.
+
We want to estimate life expectancy between 2000 and 2009, so we set a custom variable processplus = $(Process) + 2000. This returns a string, i.e. “0 + 2000”, but this isn’t what we want! In the next line, we convert it to a useful integer value: year = $INT(processplus,%d), which will now range from 2000 to 2009.
In our arguments, we append our new variable $(year).
To prevent HTCondor from rewriting outputs from each calculation over each other, _$(year) is appended to the filenames of the log, error, and output files.
Once the job is fully complete, you can check your outputs to see if it worked as expected.
+
+
Once the job is fully complete, you can check your outputs to see if it worked as expected.
+
Filenames as arguments using queue <variable> from <list>
@@ -495,13 +503,17 @@
Filenames as argu
Let’s say we want to perform our analysis on a few countries in the year 2024, but not all. Instead of creating separate submit files from each country, we can utilize HTCondor’s queue <variable> from <list> function.
-
Create text file called countries.txt. Within it, paste the following:
+
+
Create text file called countries.txt. Within it, paste the following:
+
Argentina
Brazil
Chile
-
Create a new submit script, least_squares_list.sub.
+
+
Create a new submit script, least_squares_list.sub.
+
# least_squares_list.sub - an example HTCondor submit file for passing arguments
# Specify your executable and your arguments
@@ -532,13 +544,17 @@
Filenames as argu
In our arguments line, we use the $(country) variable.