This guide asks a range of questions to consider when deciding which platform to use for your research. The suitable choice depends on your use cases and requirements.
Does the work need a lot of memory?¶
For example, a local laptop / workstation may have 4-64 GB
There may be tools and methods to reduce memory usage, e.g., SWD6: High Performance Python
High Performance Computers (HPC)
Does the work need a lot of storage?¶
Do you need to parallelise the work over many cores?¶
Do you need to use GPUs?¶
Buy a local laptop / workstation with a GPU
HPC (multiple / more powerful GPUs)
When considering costs relating to research platforms it’s important to think of cloud resources differently to on-campus hardware.
Cloud resources are typically not designed to be on all the time and all aspects of a cloud computational setup have costs associated i.e., you’ll pay for your virtual machine (VM) whilst it’s on, but you’ll also need to pay for its storage, virtual network, and associated public IP address.
Therefore, when using cloud resources it’s important to consider them as throwaway resources that you want to spin up to use, and after your experiments are complete, destroy the instance and its associated resources.
Below are some suggestions for how to initially scope costs on Azure, how to minimise your spending, and tips for monitoring spending on Azure.
Scoping costs for Azure resources
Pre-determine your cloud work schedule. Cloud costs are on a usage basis, so planning (even approximately) how many hours of compute you’ll need will make scoping your costs easier.
Use the Azure Price Calculator to generate an approximate monthly budget for your cloud spend.
Tips for minimising spending on Azure
Always turn off your VMs when you’re not using them.
When tidying up a VM setup, make sure you also delete other associated resources such as Managed Disks, public IP address, and virtual network.
Tips for monitoring spending on Azure
You can monitor your projected spend on Azure by checking the
Cost analysismenu under
Cost Managementsection on the left-hand menu when viewing a specific resource group. We encourage users to monitor this closely as especially initial costs can deviate until your setup stabilises.
You can configure specific cost alert emails be sent to you by using the
Cost alertsmenu under
Cost Managementsection on the left-hand menu when viewing a specific resource group. This allows you to create a budget for a given period and once your resources uses a percentage of the specified budget you will receive an email alert.
LASER runs using Azure for the provision of virtual machines but with some heavy technical controls in place to enable the analysis of high sensitive data in a research setting
Therefore LASER VMs or Virtual Research Environments (VREs) tend to be more permanent than a standard Azure VM which incurs more persistent costs. More details on this can be found on the LASER website
A cost estimate is available from the DAT team on request and a brief walkthrough of a basic LASER VM is detailed below. Below is an example of costs, other storage and compute specification are available and best discussed with the DAT team
LASER Standard VM
The basic assumption for usage of a LASER VM is 104 hours a month which takes into account full time usage during office hours (with adjustment for weekends, leave, and sickness).
The entry grade VM is a VMs D4s_v4 (4 vCPUs, 16 GB RAM) with 128GB of E10 Managed Disk storage.
10GB of shared storage.
Azure private link services for shared storage.
Backups for both shared and VM storage.
Additional cost for time to build and destroy the VMs.
2.5% FTE cost for support from the DAT team.
How can I use LASER?¶
Contact the Data Analytics Team at email@example.com.
How can I get an account on Bede?¶
How can I get an account on JADE-2?¶
Register on Hartree Self Service (for technical support)
Click here and use the register option in the top right-hand corner
Register on Hartree SAFE (to manage your account)
Request to join the project
From within SAFE, click “Request join project”
Select: J2AD014 - University of Leeds
An project administrator, can then provide the access code, accept you onto the project, and add you to the relevant group
More detail is here