June 30, 2022
You may be surprised how ready Python is for heterogeneous programming, and how easy it is to use today. Our first three articles about heterogeneous programming focused primarily on C++ as we ponder “how to enable programming in the face of an explosion of hardware diversity that is coming?” For a refresher on what motivates this question... Read more…
July 22, 2020
What’s your go-to programming language? As judged by IEEE Spectrum, it is (again) Python and comfortably so according to an article posted today. C++ finished Read more…
September 12, 2019
Machine learning models running on everything from cloud platforms to mobile phones are posing new challenges for developers faced with growing tool complexity. Read more…
September 9, 2019
In our world filled with unintended consequences, it turns out that saving memory space to help deal with GPU limitations, knowing it introduces performance pen Read more…
July 2, 2019
A new AI programming language seeks to ease the process of writing inference algorithms and other predictive models without the hassle of grinding out complicated equations and code. Among the goals of the probabilistic programming system dubbed “Gen” is making it easier for coding novices to write models and algorithms for broader AI applications such as computer vision and robotics. Read more…
June 17, 2019
TIOBE has released its June 2019 Index, and Python has reached another all-time high. TIOBE, which stands for “the importance of being earnest,” was founded in 2000. Its Programming Community Index – which is updated on a monthly basis... Read more…
June 10, 2019
ISC is looming fast and on the Wednesday we will be holding a panel asking the question whether it is time to focus more on the consolidation and interoperabili Read more…
March 26, 2019
AI workloads are becoming ubiquitous, including running on the world’s fastest computers — thereby changing what we call HPC forever. As every organization Read more…
Data centers are experiencing increasing power consumption, space constraints and cooling demands due to the unprecedented computing power required by today’s chips and servers. HVAC cooling systems consume approximately 40% of a data center’s electricity. These systems traditionally use air conditioning, air handling and fans to cool the data center facility and IT equipment, ultimately resulting in high energy consumption and high carbon emissions. Data centers are moving to direct liquid cooled (DLC) systems to improve cooling efficiency thus lowering their PUE, operating expenses (OPEX) and carbon footprint.
This paper describes how CoolIT Systems (CoolIT) meets the need for improved energy efficiency in data centers and includes case studies that show how CoolIT’s DLC solutions improve energy efficiency, increase rack density, lower OPEX, and enable sustainability programs. CoolIT is the global market and innovation leader in scalable DLC solutions for the world’s most demanding computing environments. CoolIT’s end-to-end solutions meet the rising demand in cooling and the rising demand for energy efficiency.
Divergent Technologies developed a digital production system that can revolutionize automotive and industrial scale manufacturing. Divergent uses new manufacturing solutions and their Divergent Adaptive Production System (DAPS™) software to make vehicle manufacturing more efficient, less costly and decrease manufacturing waste by replacing existing design and production processes.
Divergent initially used on-premises workstations to run HPC simulations but faced challenges because their workstations could not achieve fast enough simulation times. Divergent also needed to free staff from managing the HPC system, CAE integration and IT update tasks.
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