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Merge pull request #116 from NYU-RTS/ci_typos
CI: add spellchecks with typos
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.github/workflows/spellcheck.yaml

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name: Spelling
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permissions:
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contents: read
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on: [pull_request]
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env:
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CLICOLOR: 1
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jobs:
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spelling:
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name: Spell Check with Typos
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runs-on: ubuntu-latest
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steps:
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- name: Checkout Actions Repository
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uses: actions/checkout@v4
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- name: Spell Check Repo
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uses: crate-ci/typos@v1.33.1
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with:
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files: docs/**/**/*.md docs/**/**/*.mdx

_typos.toml

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[default.extend-words]
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# Scientific Software
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namd = "namd"

docs/genai/02_external_llms/01_llm_access.mdx

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Broadly it facilitates:
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- **Route requests** via configurations that can allow for fallbacks, load balance, etc
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- **Observability** via the control pane that displays your usage statistics and logs. You can retrive your logs via an API.
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- **Prompt management** via the prompt playground. You can compare the respone for a prompt across multiple LLMs, collaborate with your team and export your prompts.
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- **Observability** via the control pane that displays your usage statistics and logs. You can retrieve your logs via an API.
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- **Prompt management** via the prompt playground. You can compare the response for a prompt across multiple LLMs, collaborate with your team and export your prompts.
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- **Guardrails** usage by allowing you to define them or integrate with third party guardrails.
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- **Agentic workflows** by integrating with various agentic frameworks like langchain, llamaindex, etc.
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- **Security & Governance** by allowing you to set budget and rate limits on the API keys created for your workspace

docs/genai/05_how_to_guides/01_temperature.md

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# Temperature
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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:
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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:
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- [How to generate text: using different decoding methods for language generation with Transformers](https://huggingface.co/blog/how-to-generate)
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- [What is LLM Temperature?](https://www.ibm.com/think/topics/llm-temperature)
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:::tip
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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.
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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.
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:::
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docs/hpc/01_getting_started/02_getting_and_renewing_an_account.md

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[hpc account request form link for courses]: https://docs.google.com/forms/d/e/1FAIpQLSdehngqL1xso-YV6MOhplKNwxXjASHYnDtM_5THB3P2vrDKcg/viewform?usp=sf_link
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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.
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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.
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:::info
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- Respond promptly to account-related requests from HPC staff
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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)
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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)
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## Bulk HPC Accounts for Courses
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:::note
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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:
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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:
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```sh
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apt-get install openconnect

docs/hpc/01_getting_started/06_coldfront_requesting_an_allocation_request.md

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!["PI request allocation" section](./static/PI_request_allocation.png)
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After clicking "+Request Resource Allocation", you'll see a list of resources you can request for.
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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.
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Please select a resource and fill in justification to complete the allocation reqeust process.
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!["Univeristy HPC resource" section](./static/uni_resource.png)
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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.
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Please select a resource and fill in justification to complete the allocation request process.
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!["University HPC resource" section](./static/uni_resource.png)
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!["School-wise resource" section](./static/school_resource.png)
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Now your allocation request is created! You'll see an allocation request with "New" status.

docs/hpc/03_storage/01_intro_and_data_management.mdx

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#### HPC Vast
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The HPC Vast all-flash file system is the HPC file system where users store research data needed during the analysis phase of their research projects, particuarly for high I/O data that can bottleneck on the scratch file system. The Vast file system provides ***temporary*** storage for datasets needed for running jobs.
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The HPC Vast all-flash file system is the HPC file system where users store research data needed during the analysis phase of their research projects, particularly for high I/O data that can bottleneck on the scratch file system. The Vast file system provides ***temporary*** storage for datasets needed for running jobs.
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Files stored in the HPC vast file system are subject to the <ins>***HPC Vast old file purging policy:*** Files on the `/vast` file system that have not been accessed for **60 or more days** will be purged.</ins>
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docs/hpc/03_storage/03_data_transfers.md

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### Linux & Mac Tools
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#### scp and rsync
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:::warning
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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.
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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.
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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

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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)
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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)
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Sample commands:

docs/hpc/05_submitting_jobs/01_slurm_submitting_jobs.md

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- 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:
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- 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:
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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:
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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:
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|--------------------- INFORMATION ----------------------
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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.
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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.
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### Interactive Bash Job Examples
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