Conveners
HPC: Software Platforms
- Chair: Zama Mtshali (Technical team)
HPC: for AI and Machine Learning
- Chair: Krishna Govender (CHPC)
HPC: Education
- Chair: Bryan Johnston (CHPC)
HPC: Technology
- Chair: Themba Hlatshwayo (System Administration)
HPC: Technology
- Chair: Eric Mbele ()
HPC: Technology
- Chair: Sticks Mabakane (CENTRE FOR HIGH PERFORMANCE COMPUTING)
HPC: Storage & IO
- Chair: Lepeke Phukungoane (CHPC)
HPC: Storage & IO
- Chair: Jay Lofstead (Sandia National Laboratories)
HPC: Storage & IO
- Chair: Sean Murray (CERN/CHPC, CSIR)
HPC: Storage & IO
- Chair: Jay Lofstead (Sandia National Laboratories)
Kaldi] is an open source software project that was initiated by the Center for Language and Speech Processing,Johns Hopkins University. It is one of the leading toolkits used for research in automatic speech recognition (ASR).The toolkit employs current machine learning techniques such a deep neural networks and is capable of state-of-the-art performance. Kaldi can be ...
In this talk I'll provide some stories from leading the ChRIS computing
effort (https://chrisproject.org) over several years as it grew from
simple scripts that ran neuro-MRI analysis programs in a small lab to a
distributed container based platform that is both cloud and HPC ready
and currently actively supported by Red Hat, Inc, and their OpenShift
platform for cloud computing.
While...
NVIDIA has early identified the promising HPC – AI convergence trend and has been working on enabling it. The growing adoption of NVIDIA Ampere GPU by the Top 500 Supercomputers highlights the need of computing acceleration for this HPC & AI convergence. Many projects today demonstrate the benefit of AI for HPC, in terms of accuracy and time to solution, in many domains such as Computational...
Nowadays, many organizations are trying to find ways to converge classic HPC and AI. There are generally good reasons to do this because of significant similarities between HPC and AI workloads and workload scaling. However, for AI workloads to perform well on clusters, it is also important to be aware of the differences for AI workloads (especially DeepLearning) compared to classic HPC...
The TANGIBL coding project hosted at Nelson Mandela University Computing Sciences, aims at introducing learners to coding concepts without the use of computers. It uses mobile apps, customized tokens and image recognition to give learners the experience of actual code executing. Since 2017, over 20000 learners across the country have been reached through interactive workshops. With the...
There are arguments amongst academics and practitioners alike for the importance of countries on the African to plug into the information society. On the ground, this has resulted in an emphasis on the importance of partnerships not just within institutions of higher learning but also amongst those in industry. Internationally, we note the growth in interest of research around such...
Accelerating scientific Computing and deep learning applications with NVIDIA Mellanox In-Network Computing engines.
Budgets and management of allocations in an HPC are valuable tools that manage user behavior and the real costs associated with running an HPC either on premise or in the cloud. This talk will explain how Altair PBS Professional 2020.1 deliver these tools and will briefly demonstrate how simple and robust they are in use.
With the maturity of AI algorithms, increased computing power and explosive growth of data, manual labor has become a GPT technology that will Will Drive Social Development Profoundly. AI will also serve as an important technology, cooperating with HPC, showing its prominence in scientific research in various fields.
In spite of all the recent advances in biochemistry and several associated areas, pharmaceutical drug discovery is still notoriously difficult to do, with lives literally at stake. A typical drug interacts with 300 other enzymes and processes within the human body, and a drug has to pass with minimal disruptions to all of these processes in order to deemed safe. Nearly 90% of all targeted...
Tomorrow’s supercomputers will need to leverage the power of heterogeneous architectures in more graceful ways than what can be done today. Doing so will improve the trajectory of future performance gains.
Tsolo Storage Systems is a leading provider of petascale Ceph storage solutions. Through our partnership with the South African Radio Astronomy Observatory, we have delivered some of the largest storage installations in the country.
Our next generation product seeks to democratise the power and cost-benefit of Ceph as an open-source storage solution in order to drastically simplify your...
Moving masses of data is a challenge. In most cases networks optimized for business
operations are neither designed for nor capable of supporting the data movement requirements of data intensive research. When scientists attempt to run data intensive applications over these so called “general purpose”/enterprise networks, the result is often poor performance – in many cases poor enough that...
Traditionally, file systems are mostly monolithic, making it hard to experiment with new approaches and technologies. Exchanging core functionality within a file system is a burdensome task, leading to a lack of innovation in this area. However, data volumes are growing rapidly because the ability to capture and produce data is increasing at an exponential rate. Rising core counts and data...
Many scientific fields increasingly use high-performance computing (HPC) to process and analyze massive amounts of experimental data while storage systems in today’s HPC environments have to cope with new access patterns. These patterns include many metadata operations, small I/O requests, or randomized file I/O, while general-purpose parallel file systems have been optimized for sequential...
One goal of support staff at a data center is to identify inefficient jobs and to improve their efficiency.
Therefore, a data center deploys monitoring systems that capture the behavior of the executed jobs.
While it is easy to utilize statistics to rank jobs based on the utilization of computing, storage, and network, it is tricky to find patterns in 100.000 jobs, i.e., is there a class of...
Simulating Additive Manufacturing (AM) has been difficult because simulation domains can be extremely large and the computational load is minimal. With the way that AM works, only a small part of the simulation domain is required at any time. Stitch-IO offers a way to decompose AM simulations into a series of short runs over short time and space scales and then enables stitching together the...
This talk will cover current LANL HPC storage environments and methods, new directions and technologies being explored, and how HPC, AI, and Analytics storage workloads might be serviced by a single flexible storage system a few years from now. Additionally information on a few of the many HPC storage related R&D projects LANL and its partners is working on. Also, information on...
Scalable storage servers consist of multiple parts that communicate asynchronously via queues. There is usually a frontend that queues access requests from storage clients and uses one or more threads to forward queued requests to a backend. The backend queues these forwarded requests and batches them to efficiently use storage devices it manages. Storage servers can have multiple kinds of...
This talk by Microsoft will look at the application of HPC in the design, manufacturing and testing in the Automotive industry. Additionally we will showcase HPC, Big data and Machine learning technologies used in the testing of Autonomous driving vehicles.
