For organizations operating high-performance data centers, cooling is a significant challenge. High-end processor TDPs are also climbing with each generation, and we are rapidly approaching the point where air-cooling will become infeasible. Liquid cooling is an obvious answer but brings new challenges, including cost, maintenance issues, and concerns about leakage and safety. In a recent
Machine learning (ML) is used for multiple healthcare and life sciences (HCLS) applications, including medical imaging, protein folding, drug discovery, and gene editing. While Nextflow pipelines (like those in nf-core) are commonly used for genomics, they are also being adopted for machine learning workloads. In this artice, we explain how to build an example Nextflow
In November, timed for SuperComputing 2023, I had the opportunity to work the Altair and Intel to describe the new integration between Altair Grid Engine and Intel Data Center GPU Max series. You can learn about the integration here:
Recently I had the opportunity to work on an interesting tutorial for Seqera Labs, explaining how to adapt a machine learning inference pipeline to use an AWS Batch GPU environment provisioned using Nextflow Tower. The example uses Stable Diffusion – an open source text to image model to generate a variable number of images and
I recently had the opportunity to with Altair and AMD and contribute to an article submitted to engineering.com about creating sustainable HPC environments.
Financial institutions (FIs) face unprecedented challenges. With increasing consumer expectations and megatrends such as mobile banking, alternative lenders, and cloud computing, banks are under intense pressure. They need to innovate faster, offer new services, and deploy new applications to serve their customers better. Despite these imperatives, data center growth rates have become unsustainable. The need
Realizing a more productive environment for quantitative analysis in the financial services industry
Quantitative analysis refers to the use of mathematical and statistical modeling, measurement, and research to understand and quantify market behaviors. By studying these behaviors, analysts can develop models that predict the prices of financial instruments under different market scenarios. In this whitepaper sponsored by AMD, we present the results of a quantitaitive analysis based on
There’s perhaps no field more demanding than modern semiconductor design. In both research and commercial settings, customers expect new electronic devices to be faster, cheaper, smaller, and more energy-efficient with each generation. Semiconductor producers rely on electronic design automation (EDA) tools to realize these improvements. Few understand these challenges better than CEA Tech, the Grenoble-based
This whitepaper funded by AMD discusses current challenges in CAE and explains how AMD EPYC 7003 series processors with V-Cache technology and HPE Apollo Gen10 Plus servers are an ideal solution for manufacturers.
In today’s hyper-competitive business environment, data is at the heart of everything we do. Business leaders rely on up-to-date data to better understand their customers and competitors, make better, more informed decisions, and support new business initiatives. This paper examines some of the challenges with existing data pipelines and discuss five considerations for building a