May 22, 2023
Intel has finally provided specific details on wholesale changes it has made to its supercomputing chip roadmap after an abrupt reversal of an ambitious plan to Read more…
August 2, 2022
A new version of a standard backed by major cloud providers and chip companies could change the way some of the world's largest datacenters and fastest supercomputers are built. The CXL Consortium on Tuesday announced a new specification called CXL 3.0 – also known as Compute Express Link 3.0... Read more…
August 2, 2022
The Universal Chiplet Interconnect Express (UCIe) consortium is moving ahead with its effort to standardize a universal interconnect at the package level. The c Read more…
August 1, 2022
As the need for speed drives computational workloads, more standards organizations are coalescing around a standard called Compute Express Link – also known a Read more…
March 2, 2022
A new industry consortium aims to establish a die-to-die interconnect standard – Universal Chiplet Interconnect Express (UCIe) – in support of an open chipl Read more…
September 22, 2020
UK-based semiconductor design company Arm today teased details of its Neoverse roadmap, introducing V1 (codenamed Zeus) and N2 (codenamed Perseus), Arm’s second generation N-series platform. The chip IP vendor said the new platforms will deliver 50 percent and 40 percent more... Read more…
August 17, 2020
IBM today introduced its next generation Power10 microprocessor, a 7nm device manufactured by Samsung. The chip features a new microarchitecture, broad new memo Read more…
March 14, 2019
Another front has been opened in the long campaign to enable any-to-any connectivity in high performance datacenter computing. The Compute Express Link (CXL) consortium – with tech heavies Intel, Google, HPE, Dell EMC, Microsoft, Facebook, Cisco, Huawei and Alibaba – has ratified version 1.0 of the CXL specification... 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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