Fix all .md files

Author: s-sajid-ali

docs/genai/05_how_to_guides/01_temperature.md

@@ -1,12 +1,12 @@
 # Temperature
 
-Generating text (or images) from LLMs is inherently probabilistic. However, as an end user you have many parameters at your disposal to tweak the behavior of LLMs. Of these, temperature is the most commonly used. Broadly, it controls the randonmess of the generated text. A lower temperature produces more deterministic outputs, while a higher temperature produces more random "creative" output. For a more comprehensive explanation on this topic, refer to the following:
+Generating text (or images) from LLMs is inherently probabilistic. However, as an end user you have many parameters at your disposal to tweak the behavior of LLMs. Of these, temperature is the most commonly used. Broadly, it controls the randomness of the generated text. A lower temperature produces more deterministic outputs, while a higher temperature produces more random "creative" output. For a more comprehensive explanation on this topic, refer to the following:
 -   [How to generate text: using different decoding methods for language generation with Transformers](https://huggingface.co/blog/how-to-generate)
 -   [What is LLM Temperature?](https://www.ibm.com/think/topics/llm-temperature)
 
 :::tip
 
-The effect of temperature is probabalistic, so you might need to run the script repeatedly to obtain a representative sample of generated text from the LLM.
+The effect of temperature is probabilistic, so you might need to run the script repeatedly to obtain a representative sample of generated text from the LLM.
 
 :::
 

docs/hpc/01_getting_started/02_getting_and_renewing_an_account.md

@@ -8,7 +8,7 @@
 
 [hpc account request form link for courses]: https://docs.google.com/forms/d/e/1FAIpQLSdehngqL1xso-YV6MOhplKNwxXjASHYnDtM_5THB3P2vrDKcg/viewform?usp=sf_link
 
-This section deals with the eligibility for getting HPC accounts and the process to create new ones, renew existing oaccountsThis section deals with the eligibility for getting HPC accounts, the process to create new accounts, renew existing ones and touches on access policies after graduation fom NYU and access for non-NYU researchers.
+This section deals with the eligibility for getting HPC accounts and the process to create new ones, renew existing oaccountsThis section deals with the eligibility for getting HPC accounts, the process to create new accounts, renew existing ones and touches on access policies after graduation from NYU and access for non-NYU researchers.
 
 :::info
 
@@ -61,7 +61,7 @@ HPC faculty sponsors are expected to:
 
 -   Respond promptly to account-related requests from HPC staff
 
-Each year, your sponosred users must renew their account. You will need to approve the renewal by logging into the [NYU Identity Management service][nyu ims link]. We have a [walkthrogh of the approval process here](./03_walkthrough_approve_hpc_account_request.md)
+Each year, your sponsored users must renew their account. You will need to approve the renewal by logging into the [NYU Identity Management service][nyu ims link]. We have a [walkthrogh of the approval process here](./03_walkthrough_approve_hpc_account_request.md)
 
 ## Bulk HPC Accounts for Courses
 
@@ -95,7 +95,7 @@ If you are not part of a collaboration, your access to cluster will end together
 
 :::note
 
-In order to request a new HPC account or renew an expired one, you need to be connected to the NYU VPN if you are working remotely, Please see [instructions on how to install and use the NYU VPN][nyu vpn link]. Linux clients are not officially supported, however we were able to successfully use openVPN client. Here are installation and connection instructions for a debian linux distribution with apt pacakge manager:
+In order to request a new HPC account or renew an expired one, you need to be connected to the NYU VPN if you are working remotely, Please see [instructions on how to install and use the NYU VPN][nyu vpn link]. Linux clients are not officially supported, however we were able to successfully use openVPN client. Here are installation and connection instructions for a debian linux distribution with apt package manager:
 
 ```sh
 apt-get install openconnect

docs/hpc/01_getting_started/06_coldfront_requesting_an_allocation_request.md

@@ -11,9 +11,9 @@ If you scroll down a bit, you'll see "+Request Resource Allocation" button.
 !["PI request allocation" section](./static/PI_request_allocation.png)
 
 After clicking "+Request Resource Allocation", you'll see a list of resources you can request for.
-Basically, you'll see general "Univeristy HPC" which is default for all and school-wise resources (e.g., Tandon(Genric)) based on a school that your project belongs to.
-Please select a resource and fill in justification to complete the allocation reqeust process.
-!["Univeristy HPC resource" section](./static/uni_resource.png)
+Basically, you'll see general "University HPC" which is default for all and school-wise resources (e.g., Tandon(Generic)) based on a school that your project belongs to.
+Please select a resource and fill in justification to complete the allocation request process.
+!["University HPC resource" section](./static/uni_resource.png)
 !["School-wise resource" section](./static/school_resource.png)
 
 Now your allocation request is created! You'll see an allocation request with "New" status.

docs/hpc/03_storage/03_data_transfers.md

@@ -33,7 +33,7 @@ logout
 ### Linux & Mac Tools
 #### scp and rsync
 :::warning
-Please use Data Transfer Nodes (DTNs) with these tools. While one can transfer data while on login nodes, it is  considered a bad practice because it can degrate the node's performance.
+Please use Data Transfer Nodes (DTNs) with these tools. While one can transfer data while on login nodes, it is  considered a bad practice because it can degrade the node's performance.
 :::
 
 Sometimes these two tools are convenient for transferring small files. Using the DTNs does not require to set up an SSH tunnel; use the hostname `dtn.hpc.nyu.edu` for one-step copying. See below for examples of commands invoked on the command line on a laptop running a Unix-like operating system:

docs/hpc/03_storage/08_transferring_cloud_storage_data_with_rclone.md

@@ -344,7 +344,7 @@ Please enter 'q' and we're done with configuration.
 
 ### Step 4: Transfer
 :::warning
-Please be sure to perform data transters on a data transfer node (DTN).  It can degrade performace for other users to perform transfers on other types of nodes.  For more information please see [Data Transfers](./03_data_transfers.md)
+Please be sure to perform data transters on a data transfer node (DTN).  It can degrade performance for other users to perform transfers on other types of nodes.  For more information please see [Data Transfers](./03_data_transfers.md)
 :::
 
 Sample commands:

docs/hpc/05_submitting_jobs/01_slurm_submitting_jobs.md

@@ -312,7 +312,7 @@ or as a command-line option to sbatch when you submit the job:
 ### Options for running many similar jobs
 
 -   `-a, --array=indexes`
-    -   Submit an array of jobs with array ids as specified. Array ids can be specified as a numerical range, a comma-seperated list of numbers, or as some combination of the two. Each job instance will have an environment variable `SLURM_ARRAY_JOB_ID` and `SLURM_ARRAY_TASK_ID`. For example:
+    -   Submit an array of jobs with array ids as specified. Array ids can be specified as a numerical range, a comma-separated list of numbers, or as some combination of the two. Each job instance will have an environment variable `SLURM_ARRAY_JOB_ID` and `SLURM_ARRAY_TASK_ID`. For example:
     -   `--array=1-11`, to start an array job with index from 1 to 11
     -   `--array=1-7:2`, to submit an array job with index step size 2
     -   `--array=1-9%4`, to submit an array job with simultaneously running job elements set to 4
@@ -489,7 +489,7 @@ cd /scratch/$USER/myambertest
 pmemd.cuda -O
 ```
 
-The demo Amber job should take ~2 minutes to finish once it starts runnning. When the job is done, several output files are generated. Check the one named "mdout", which has a section most relevant here:
+The demo Amber job should take ~2 minutes to finish once it starts running. When the job is done, several output files are generated. Check the one named "mdout", which has a section most relevant here:
 
 ```sh
 |--------------------- INFORMATION ---------------------- 
@@ -599,7 +599,7 @@ If you do not request resources you will get the default settings. If after some
     -   Enable X forwarding, so programs using a GUI can be used during the session (provided you have X forwarding to your workstation set up)
     -   To leave an interactive batch session, type `exit` at the command prompt
 
-Certain tasks need user iteraction - such as debugging and some GUI-based applications. However the HPC clusters rely on batch job scheduling to efficiently allocate resources. Interactive batch jobs allow these apparently conflicting requirements to be met.
+Certain tasks need user interaction - such as debugging and some GUI-based applications. However the HPC clusters rely on batch job scheduling to efficiently allocate resources. Interactive batch jobs allow these apparently conflicting requirements to be met.
 
 ### Interactive Bash Job Examples
 

docs/hpc/05_submitting_jobs/02_slurm_main_commands.md

@@ -112,7 +112,7 @@ man squeue # for more information
 | ------- | ----------- |
 | `--me` | Prints queued jobs for the current user |
 | `--user` | Prints queued jobs under a specific user, or a comma list of users |
-| `--job` | Specify a comma seperated list of job IDs to display |
+| `--job` | Specify a comma separated list of job IDs to display |
 | `--help` | Print a help message describing all options squeue |
 
 ## sacct

docs/hpc/05_submitting_jobs/03_slurm_tutorial.md

@@ -6,7 +6,7 @@ In a High Performance Computing Cluster, such as the NYU-IT HPC Greene cluster,
 
 Linux operating system ( in our case Red Hat Enterprise Linux) runs on each of the nodes individually. The resources are shared among many users for their technical or scientific computing purposes.
 
-Slurm is a cluster software layer built on top of the interconnected nodes, aiming at orchestrating the nodes' computing activites, so that the cluster could be viewed as a unified, enhanced and scalable computing system by its users.
+Slurm is a cluster software layer built on top of the interconnected nodes, aiming at orchestrating the nodes' computing activities, so that the cluster could be viewed as a unified, enhanced and scalable computing system by its users.
 
 In NYU HPC clusters the users coming from many departments with various disciplines and subjects, with their own computing projects, impose on us very diverse requirements regarding hardware, software resources, and processing parallelism. Users submit jobs, which compete for computing resources.
 
@@ -24,7 +24,7 @@ For an overview of useful Slurm commands, please read [Slurm Main Commands](./02
 
 ## Software and Environment Modules
 
-Lmod, an Environment Module system, is a tool for managing multiple versions and configurations of software packages and is used by many HPC centers around the world. With Environment Modules, software packages are installed away from the base system directories, and for each pacakge, an associated modulefile describes what must be altered in a user's shell environment - such as the $PATH environment variable - in order to use the software package. The modulefile also describes dependencies and conflicts between this software package and other packages and versions.
+Lmod, an Environment Module system, is a tool for managing multiple versions and configurations of software packages and is used by many HPC centers around the world. With Environment Modules, software packages are installed away from the base system directories, and for each package, an associated modulefile describes what must be altered in a user's shell environment - such as the $PATH environment variable - in order to use the software package. The modulefile also describes dependencies and conflicts between this software package and other packages and versions.
 
 To use a given software package, you load the corresponding module. Unloading the module afterwards cleanly undoes the changes that loading the modules made to your environment, thus freeing you to use other software packages that might have conflicted with the first one.
 
@@ -135,7 +135,7 @@ You can submit the job with the following command:
 sbatch myscript.sbatch
 ```
 
-The command will result in the job queuing as it awaits resources to become available (which varies on the number of other jobs being run on the cluster and the resources requested). You can see the status of yor jobs with the following command:
+The command will result in the job queuing as it awaits resources to become available (which varies on the number of other jobs being run on the cluster and the resources requested). You can see the status of your jobs with the following command:
 
 ```sh
 squeue --me

docs/hpc/06_tools_and_software/02_conda_environments.md

@@ -145,7 +145,7 @@ If you installed extra packages using pip (Python)
 
 In this you can use
 ```sh
-export PYTHONNOUSERSITE=True  ## to ingnore packages in ~/.local/lib/python<version>
+export PYTHONNOUSERSITE=True  ## to ignore packages in ~/.local/lib/python<version>
 # save
 conda list --export > conda_requirements.txt
 pip freeze > pip_requirements.txt
@@ -162,7 +162,7 @@ However, this may fail if your conda environment is created as a sub-directory o
 
 Installed extra packages using install.packages? (R)
 
-Usecase: You need packages not availalbe in conda channels, and want to use install.packages.
+Usecase: You need packages not available in conda channels, and want to use install.packages.
 
 Command `conda list --export` will not include packages installed by "install.packages". So, do not use `conda install` at all. To have reproducibility in this case you need to use Conda and renv together, as described below
 

docs/hpc/06_tools_and_software/07_sqlite_handling_large_structured_data.md

@@ -10,7 +10,7 @@ Storing your data in the [SQLite](https://www.sqlite.org/index.html) format allo
 ### Some use-cases
 
 -   You think you need MySQL, PostreSQL, etc for your ML project. Usually you don't
--   You have to deal with hundreds of GB of table-stuctured data (or larger) and your script (for whatever reason) can't be made parallel.
+-   You have to deal with hundreds of GB of table-structured data (or larger) and your script (for whatever reason) can't be made parallel.
 -   You would request a lot of RAM and work with data slowly.
 :::warning
 This would be a waste of RAM.