Reviving Temporary Directories: Local SSH & Storage Insights

Hey everyone! Let's dive into something that might seem a bit dusty at first glance: temporary directories and local storage, especially when we're talking about high-performance computing (HPC) environments. I know, I know, the word "deprecated" can send shivers down your spine, but stick with me! We're going to unearth some valuable nuggets from an old page on the NeSI documentation (Link to the page containing the erratum), and figure out how they still apply today. Think of it as a treasure hunt where the treasure is a better understanding of how to use local storage effectively. This will also cover the local SSH which is often the key to access those directories.

Understanding Temporary Directories and Their Importance

Okay, first things first: what exactly are temporary directories, and why should you care? Well, imagine you're running a super complex simulation or crunching massive datasets. You need a place to store intermediate files, scratch data, or anything that doesn't need to be permanently saved. That's where temporary directories come in. They provide a fast, often local, storage space for these files. This can significantly speed up your computations by reducing the time it takes to read and write data. The key is to understand how to access these.

Think of it like this: instead of writing to your slow, long-term hard drive, you're using a super-speedy temporary workspace. It's like having a lightning-fast desk to work on instead of a cluttered, slow one. This can make a huge difference, especially for I/O-intensive tasks. And let's be honest, time is money, especially when you're dealing with HPC resources! Properly using these directories can also free up space on the shared file systems, making everyone's life easier. The original documentation does a good job of outlining the concept of a temporary directory, and how it relates to the larger system. Remember, a well-optimized workflow is a happy workflow, and leveraging temporary directories is a key part of that.

When working in a HPC environment, it's common for each compute node to have a local storage device, often a Solid State Drive (SSD). This local storage is incredibly fast compared to the network-attached storage that typically holds your home directory and project directories. Using this local storage for temporary files can dramatically reduce the runtime of your jobs, especially those that involve a lot of reading and writing of intermediate data. The most common environment variable used to point to this local, temporary storage is $TMPDIR. The system often sets this variable automatically when you request local disk resources. But we'll get more into the specifics of requesting local disk later.

The Benefits of Using Temporary Directories

• Speed: Local storage is usually much faster than network storage.
• Efficiency: Reduces load on shared file systems.
• Cost: Sometimes, using temporary storage can be more cost-effective than using more expensive shared storage.
• Performance: Faster I/O operations can lead to significant performance gains in your computations.

Navigating the Deprecated Page: What's Still Relevant?

Now, let's get to the heart of the matter: that deprecated page. Yeah, it's marked as outdated, but don't let that scare you away! Some of the information in there is still totally relevant and useful. The key is to extract the useful details, adapt them to the modern HPC environment, and get a better understanding. I'm talking about things like requesting local disk using --gres=ssd and the automatic setting of the $TMPDIR environment variable. These concepts are definitely still applicable and incredibly important.

The Importance of --gres=ssd

When you submit a job to an HPC system, you're typically requesting resources like CPUs, memory, and sometimes, specific hardware like GPUs. The --gres=ssd flag is how you request access to the local SSD on the compute node. This is crucial for using temporary directories effectively. Without requesting local disk, you might end up using the default, slower temporary directory on network storage, defeating the whole purpose! It's like trying to race a sports car on a gravel road.

The --gres=ssd flag tells the job scheduler to allocate a compute node with an SSD to your job. You can then use $TMPDIR to point your applications to use the local SSD for temporary files. Remember to consult the specific documentation for the HPC system you are using, as the exact syntax for requesting local disk might vary. In many systems, you might also specify the size of the SSD you need, for example, --gres=ssd:100G. This would request an SSD with 100 GB of space. It's like telling the system how big of a desk you need to work on. Understanding how to use --gres=ssd is a cornerstone of optimizing your jobs for performance.

Understanding $TMPDIR

The $TMPDIR environment variable is your key to using temporary directories. The system often sets this variable automatically when you request local disk resources (using --gres=ssd). $TMPDIR points to a directory on the local SSD. Any files you write to this directory will be stored on the fast local storage, allowing for faster I/O operations. This is where your intermediate files, scratch data, and other temporary files go. It's good practice to check the value of $TMPDIR in your job script to confirm where your temporary files are being written. It could be used to create a new directory. Make sure to remove the contents or the directory itself at the end of your job to ensure it is clean and not taking up space.

By combining --gres=ssd and $TMPDIR, you're setting up a powerful system for maximizing the speed of your computations. You are using the best tools at your disposal to create and process files in the system, so that your job runs faster.

Cleaning Up and Modernizing: Where to Go From Here

So, what's the takeaway? We've seen that while the original page might be deprecated, the concepts are not! We can still use the knowledge about --gres=ssd and $TMPDIR to optimize our jobs. But how do we move forward? I think it would be super helpful if this information could be cleaned up, updated, and integrated into the Storage or Filesystem and Quotas section of the documentation. It would make the information much easier to find and use, and improve the user experience. This kind of information is incredibly important for users to get the best out of the system.

Let's make sure that the documentation clearly explains how to:

• Request local disk using the appropriate flags (like --gres=ssd).
• Understand and utilize the $TMPDIR environment variable.
• Manage temporary files and directories effectively (e.g., cleaning up after your jobs).

Advanced Topics and Further Considerations

File System Performance

Beyond the use of local SSDs and $TMPDIR, understanding file system performance is crucial for optimizing your workflows. Different file systems have different characteristics, such as read/write speeds, the ability to handle many small files, and the overhead associated with metadata operations. The file system on the local SSD, for example, will likely be optimized for speed, but might have limitations on the total amount of storage or the number of files that can be stored. The shared file systems on the other hand, might be slower, but provide a larger amount of storage and better data durability. Considering these factors can help you choose the best storage location for your data and optimize your I/O operations.

Monitoring I/O

Monitoring I/O is an important aspect of performance tuning. Tools such as iostat and iotop can be used to monitor disk I/O activity on the compute nodes. This allows you to identify I/O bottlenecks in your applications and determine whether you are utilizing the local SSD effectively. If your application is not making full use of the local disk, you might want to review your I/O strategy and consider optimizing how your application writes data. Knowing how to monitor I/O is critical to ensure you are getting the most out of the system.

Parallel File Systems

Parallel file systems, such as Lustre, are commonly used in HPC environments to provide high-performance shared storage. Understanding how parallel file systems work can help you optimize your data access patterns and improve the overall performance of your jobs. For example, you might want to stripe your data across multiple disks to increase the aggregate bandwidth. Being knowledgeable of the best practices when working with these file systems will help you avoid bottlenecks, which could severely limit your performance.

Conclusion: Embrace the Temporary, Embrace the Speed!

So there you have it! Even though the original page is deprecated, the concepts of temporary directories and local storage are more relevant than ever. By understanding how to use --gres=ssd and $TMPDIR, you can give your computations a serious performance boost. And that means faster results, happier users, and more efficient use of valuable HPC resources. Keep an eye on those documentation updates, and don't be afraid to experiment with temporary storage to find the optimal configuration for your specific needs. The key takeaway here is that by understanding and utilizing temporary directories and local storage, you can significantly improve the performance of your HPC jobs and make the most of the available resources.

For more detailed information on storage best practices and the specifics of the NeSI environment, I recommend checking out the NeSI documentation. They're always updating their resources, so stay tuned for the latest tips and tricks! You'll become a local storage ninja in no time!

External Links

• NeSI Documentation: https://docs.nesi.org.nz/ - This is your go-to resource for all things NeSI, including detailed information on storage, job submission, and software environments.