» Handy Tools Customised for HPC Parallel Computing
By Wang Junhong, Research Computing, NUS IT on 21 Oct, 2019
When you start to work on a high-performance computing (HPC) cluster to submit and run your computational jobs, you may want to know the available job queues for job submission and the load status in these queues in order to select an appreciate queue. After jobs are submitted and running in the queues, you may also want to know the computing speed and parallel computing performance of the jobs. Your program may generate a lot of data sets or result files which occupy large amount of storage space, so you may want to know the available storage space allocated to you and the usage.
» AI for HPC Cloud Resource Recommendation – An Internship Project at NUS IT
By Choong Wey Yeh, Lucas on 21 Oct, 2019
The High Performance Computing (HPC) team at NUS IT provides services and resources for users to run large-scale computational jobs. These jobs range from machine learning programs to simulation programs by users from various departments. However, users may not always know the right amount of computational resources to request for their jobs, often resulting in resources requested being underutilised. With more resources requested than utilised, more unused resources are hogged on the HPC clusters than necessary which results in longer queueing times for other users waiting for their turn to run jobs.
» Tensorflow Model Zoo Models on NUS HPC Containers
By Ku Wee Kiat, Research Computing, NUS IT on 21 Oct, 2019
Tensorflow provides pre-built and pre-trained models in the Tensorflow Models repository for the public to use.
The official models are a collection of example models that use TensorFlow’s high-level APIs. They are intended to be well-maintained, tested, and kept up to date with the latest stable TensorFlow API. They should also be reasonably optimised for fast performance while still being easy to read.
» Subscribing to HPC Resources in the Cloud
By Yeo Eng Hee, Research Computing, NUS IT on 21 Oct, 2019
In our previous newsletter, we described how some of our HPC clusters in the shared resource pool are now running with compute nodes from the cloud. This was made possible with the implementation of a virtual private network between NUS and AWS, our cloud solution provider, extending our HPC into the cloud in a seamless manner. Job scheduling is still managed by PBS Pro, and the usual queuing is still necessary to ensure that jobs are scheduled in the cloud compute nodes in a fair manner.
» Singularity DYOI (Do Your Own Image)
By Vamshidhar Gangu, HPC Specialist, Research Computing, NUS IT on 21 Oct, 2019
The major crisis in research is reproducibility. How can one make sure to install the exact same software with its dependencies and ensure it produces the same output?
Register for HPC
» HPC Options for Research
By Tan Chee Chiang, Research Computing, NUS IT on 21 Oct, 2019
With the recent partnership confirmation between NUS and AWS, researchers can now have a more extensive range of High Performance Computing (HPC) options to consider for their research computing needs. We will review some of these options.
NUS Bug Bounty Challenge Scope and Rules
NUS IT is excited to announce the NUS Bug Bounty Program, an initiative to improve our cybersecurity awareness and posture through community effort. Partnering with HackerOne and SOC, we aim to expose ALL NUS students to ethical hacking through online games, sharing by hackers and discovering bugs on NUS production systems. Sign up now!
SAP-Oracle 12c Database Baseline Security Standard 1.0
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