In this special guest feature, our friends over at Inspur write that for new workloads that are highly compute intensive, accelerators are often required. Accelerators can speed up the computation and allow for AI and ML algorithms to be used in real time. Inspur is a leading supplier of solutions for HPC and AI/ML workloads.
Optimizing in a Heterogeneous World is (Algorithms x Devices)
November 11, 2019 by Leave a Comment
In this guest article, our friends at Intel discuss how CPUs prove better for some important Deep Learning. Here’s why, and keep your GPUs handy! Heterogeneous computing ushers in a world where we must consider permutations of algorithms and devices to find the best platform solution. No single device will win all the time, so we need to constantly assess our choices and assumptions.
A Liquid Cooling Petascale Supercomputing Site and GROMACS Workload Optimization Benchmark
October 31, 2019 by Leave a Comment
Accelerated computing have been viewed as revolutionary breakthrough technologies for AI and HPC workloads. Significant accelerated computing power from GPUs paired with CPUs is the major contributor. Our friends over at Quanta Cloud Technology (QCT) provide QuantaGrid D52G-4U 8 NVLink GPUs servers with a liquid cooling platform successfully adopted by the National Center of High-performance Computing (NCHC) in Taiwan) for their Taiwania-II project. Rank 23rd on the Top500 as of June 2019.
Deep Learning for Natural Language Processing – Choosing the Right GPU for the Job
October 23, 2019 by Leave a Comment
In this new whitepaper from our friends over at Exxact Corporation we take a look at the important topic of deep learning for Natural Language Processing (NLP) and choosing the right GPU for the job. Focus is given to the latest developments in neural networks and deep learning systems, in particular a neural network architecture called transformers. Researchers have shown that transformer networks are particularly well suited for parallelization on GPU-based systems.
Deep Learning for Natural Language Processing – Choosing the Right GPU for the Job
In this new whitepaper from our friends over at Exxact Corporation we take a look at the important topic of deep learning for Natural Language Processing (NLP) and choosing the right GPU for the job. Focus is given to the latest developments in neural networks and deep learning systems, in particular a neural network architecture called transformers. Researchers have shown that transformer networks are particularly well suited for parallelization on GPU-based systems.
GPUs for Oil and Gas Firms: Deriving Insights from Petabytes of Data
April 22, 2019 by Leave a Comment
Adoption of GPU-accelerated computing can offer oil and gas firms significant ROI today and pave the way to gain additional advantage from future technical developments. To stay competitive, these companies need to be able to derive insights from petabytes of sensor, geolocation, weather, drilling, and seismic data in milliseconds. A new white paper from Penguin Computing explores how GPUs are spurring innovation and changing how hydrocarbon businesses address data processing needs.
GPUs Address Growing Data Needs for Finance & Insurance Sectors
April 12, 2019 by Leave a Comment
A new whitepaper from Penguin Computing contends “a new era of supercomputing” has arrived — driven primarily by the emergence of graphics processing units or GPUs. The tools once specific to gaming are now being used by investment and financial services to gain greater insights and generate actionable data. Learn how GPUs are spurring innovation and changing how today’s finance companies address their data processing needs.
Exploring the ROI Potential of GPU Supercomputing
March 26, 2019 by Leave a Comment
The growing prevalence of artificial intelligence and machine learning is putting heightened focus on the quantities of data that organizations have recently accumulated — as well as the value potential in this data. Companies looking to gain a competitive edge in their market are turning to tools like graphic processing units – or GPUs – to ramp up computing power. That’s according to a new white paper from Penguin Computing.
How Financial Services Can Fuel Innovation with GPU Computing
The financial services and insurance sector is one of the most data-intensive industries in modern business. Unfortunately, that abundance of information has hindered the extraction of business value from data. However, improvements in technology can take data-related challenges that had, until recently, been considered impossible to overcome. Download the new white paper from Penguin Computing that highlights how financial services and insurance firms can benefit from GPU computing and spur innovation and future technological developments.
How Oil and Gas Firms Can Create Competitive Advantage with GPU-Accelerated Computing
Previously, oil and gas firms relied on costly, central processing unit (CPU) intensive infrastructure to manage data usage and analysis speed. GPUs for oil and gas firms have given rise to a new set of opportunities. Download the new report from Penguin Computing outlines how the adoption of GPU-accelerated computing can offer oil and gas firms significant return on investment (ROI) today and pave the way to gain additional advantage from future technical developments.
