August 22, 2022
Amid the high-performance GPU turf tussle between AMD and Nvidia (and soon, Intel), a new, China-based player is emerging: Biren Technology, founded in 2019 and headquartered in Shanghai. At Hot Chips 34, Biren co-founder and president Lingjie Xu and Biren CTO Mike Hong took the (virtual) stage to detail the company’s inaugural product: the Biren BR100 general-purpose GPU (GPGPU). “It is my honor to present... Read more…
June 12, 2019
In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programmin Read more…
September 18, 2014
Over the last decade, GPU-acceleration techniques have infiltrated the high-end of supercomputing, but increased adoption of GPUs is occurring in other compute- Read more…
August 20, 2014
Today marks the official release of the NVIDIA CUDA Toolkit version 6.5, which had previously been only available in its pre-release form. In a company blog pos Read more…
August 13, 2014
Technology, like other facets of life, commonly experiences cycles of rapid change followed by periods of relative stability. Computing has entered a stage of i Read more…
July 31, 2014
Over at the Typhoon Computing blog, Michel Müller addresses a topic that is top of mind to many HPC programmers: porting code to accelerators. Fortran p Read more…
May 29, 2014
The past decade has seen a sharp rise in heterogenous computing, processing or coprocessing using more than one processor type. One of the most prominent examp Read more…
September 5, 2013
When it comes to employing physics in medicine, there are two major fields in terms of their relevance in clinical practice: medical imaging and radiation therapy. An Argentinian research duo addresses how these domains can benefit from high-performance computing techniques... Read more…
The increasing complexity of electric vehicles result in large and complex computational models for simulations that demand enormous compute resources. On-premises high-performance computing (HPC) clusters and computer-aided engineering (CAE) tools are commonly used but some limitations occur when the models are too big or when multiple iterations need to be done in a very short term, leading to a lack of available compute resources. In this hybrid approach, cloud computing offers a flexible and cost-effective alternative, allowing engineers to utilize the latest hardware and software on-demand. Ansys Gateway powered by AWS, a cloud-based simulation software platform, drives efficiencies in automotive engineering simulations. Complete Ansys simulation and CAE/CAD developments can be managed in the cloud with access to AWS’s latest hardware instances, providing significant runtime acceleration.
Two recent studies show how Ansys Gateway powered by AWS can balance run times and costs, making it a compelling solution for automotive development.
Five Recommendations to Optimize Data Pipelines
When building AI systems at scale, managing the flow of data can make or break a business. The various stages of the AI data pipeline pose unique challenges that can disrupt or misdirect the flow of data, ultimately impacting the effectiveness of AI storage and systems.
With so many applications and diverse requirements for data types, management systems, workloads, and compliance regulations, these challenges are only amplified. Without a clear, continuous flow of data throughout the AI data lifecycle, AI models can perform poorly or even dangerously.
To ensure your AI systems are optimized, follow these five essential steps to eliminate bottlenecks and maximize efficiency.
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