54:07

The Emergence of WebAssembly (Wasm) in Scientific Computing

53:08

Exploring Compute Usage from User Facing Portals on the National Clusters

21:42

Compute Ontario Summer School 2024

01:04:42

Data Wrangling with Tidyverse (part 2)

25:31

Accelerating data analytics with RAPIDS cuDF

59:04

Accelerating Graph Analysis on GPUs

38:59

Make: a declarative, lazy, parallel workload manager. Elegant or obsolete?

51:21

Debugging your code with DDT

56:16

MySQL Part 3: Constraints and Joins

39:09

Introduction to GPU programming with OpenMP

40:03

False Sharing and Contention in Parallel Codes

41:52

Skorch: Training PyTorch models with scikit-learn

48:49

Squeeze more juice out of a single GPU in deep learning

41:06

Generalized End to End Python and Neuroscience Workflows on a Compute Cluster

46:41

p2rng – A C++ Parallel Random Number Generator Library for the Masses

50:21

Exploring job wait times on Alliance compute clusters: a holistic view

56:10

Data Wrangling with Tidyverse

43:51

Automating scientific workflows with AiiDA

41:50

DIY job monitoring, from cache misses to CO2 footprint

41:26

Leveraging the power of Linux on Windows with WSL

48:34

Contrastive learning

40:28

Modern Approaches to Profiling in Python with Scalene

55:08

CUDA, ROCm, oneAPI – All for One or One for All?

51:40

Running MATLAB on Alliance's Clusters

48:53

Before and after submitting Octave/Matlab jobs on the clusters

01:00:10

Plotnine: R's Grammar of Graphics in Python

59:42

Accelerated DataFrame with Dask-cuDF on multiple GPUs

39:21

An introduction to MPLAPACK, a multi-precision linear algebra library

33:12

How Research Data Management (RDM) Intersects with ARC and Why Should I Care?

52:39

New User Seminar

43:00

Performance: current and upcoming systems

34:01

Which GPU should I use?

01:02:13

Deploying a simple Express.js Web App

50:34

Video Editing with KDEnLive

56:09

Profiling & Performance Tuning CPU Programs

47:42

Strategies For Managing Filesystem Quotas

55:01

Transfer Learning with Tensorflow Hub

39:14

Creating and Distributing Python Packages

53:22

Remote Development on Clusters with VSCode - Part II

56:30

Debugging with ParaView

50:00

Visualizing job properties for wait time assessment

01:05:32

Working with Jupyter on Clusters

51:23

Running PyTorch codes with multi-GPU/nodes on national systems

52:04

Realtime display with Gnuplot

38:42

Speeding up Python code with Numba

52:28

Profiling GPU codes with Nsight

38:01

Demystifying Web Portals

40:42

10 ways to optimize your workflow

01:03:14

Apptainer

58:47

Using Tensorboard to debug and profile neural network models

01:10:33

More Options for Solving Jobs with Many Tasks

45:52

Gaussian16 and NBO7 on Graham and Cedar

43:32

Conquering the Scheduler

01:02:23

From histograms to dashboards: An introduction to data visualization with Python

58:58

Remote Development on Clusters with VSCode - Part I

01:15:15

Introduction to Eclipse Part 3 - Debugging MPI code

50:04

Tips for identifying when job wait times can be reduced by job submission parameter changes

54:40

The Layered Grammar of Graphics (ggplot2/plotnine)

45:18

Running machine learning example (MNIST) on multi-cores/nodes in Graham

03:29

How to add an SSH key to CCDB (Mac users)