April 15, 2024
As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…
January 20, 2015
The smartphone has already usurped the role of the computer in a number of ways, whether you use it for navigation, to check the weather, or take and share phot Read more…
January 28, 2014
Scientists at Stanford devised a "virtual earthquake" technique capable of predicting the effects of a major quake occurring along the southern San Andreas Faul Read more…
September 27, 2013
A new computer made of carbon nanotubes, created by a team of Stanford engineers, may be the first serious silicon challenger. Read more…
August 2, 2013
Stanford University will receive $16 million over the next five years from the National Nuclear Security Administration (NNSA) to use supercomputers to find ways to increase the efficiency of solar energy concentrators. The research project involves developing new models that will help solve vexing engineering challenges on the next generation of exascale supercomputers. Read more…
January 28, 2013
The 20 petaflop, third-generation IBM BlueGene system, Sequoia, may be the number two supercomputer according to the latest TOP500 rankings, but when it comes to max core usage, Sequoia has apparently set a new record. A team of Stanford engineers harnessed one million of Sequoia's nearly 1.6 CPUs in parallel to solve a sophisticated fluid dynamics problem. Read more…
May 16, 2012
Chief scientist discusses memory stacks, interconnects, and US technology leadership. Read more…
May 31, 2011
Projects like the Sloan Digital Sky Survey have provided a wealth of cosmological data for scientists to explore in detail. However, making use of those terabytes -- and generating far more data in the process of simulating and analyzing new concepts -- is highlighting the bottlenecks for scientific computing at massive scale. Read more…
In this era, expansion in digital infrastructure capacity is inevitable. Parallel to this, climate change consciousness is also rising, making sustainability a mandatory part of the organization’s functioning. As computing workloads such as AI and HPC continue to surge, so does the energy consumption, posing environmental woes. IT departments within organizations have a crucial role in combating this challenge. They can significantly drive sustainable practices by influencing newer technologies and process adoption that aid in mitigating the effects of climate change.
While buying more sustainable IT solutions is an option, partnering with IT solutions providers, such and Lenovo and Intel, who are committed to sustainability and aiding customers in executing sustainability strategies is likely to be more impactful.
Learn how Lenovo and Intel, through their partnership, are strongly positioned to address this need with their innovations driving energy efficiency and environmental stewardship.
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.
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