July 18, 2011
Microsoft announced this week that it would be offering its Project Daytona up for scrutiny--an iterative MapReduce framework that they hope will bring researchers flocking to their cloud service. Read more…
April 14, 2011
A team of researchers from Indiana University has performed an analysis of performance and other advantages and problems with existing virtualization technology options. Read more…
January 25, 2011
In this interview with Kate Keahey from Argonne National Lab, we discuss her background with distributed computing, limitations of the grid, challenges and benefits of cloud computing for HPC and her view on critical elements that the community as a whole—vendor, users, and scientists alike—will need to address as the space matures. Read more…
December 10, 2010
Microsoft has announced it is extending another round of free access to its Azure cloud platform, this time to scientific research projects in Australia. Read more…
October 19, 2010
Last week at their eScience Workshop at the University of California, Berkeley Microsoft Research announced two key technological progress points related to their Azure cloud. The advancements are currently serving researchers in ecological studies as well as biology and further demonstrate the potential of their cloud offering in further scientific computing projects. Read more…
October 18, 2010
Last year Cornell University and Purdue University received funding from the National Science Foundation to undertake their MATLAB on the TeraGrid project. Since its inception a number of researchers have been making use of the resource and Cornell's Center for Advanced Computing is demonstrating that the resource might have a permanent place in the TeraGrid resource provider collection in the future. Read more…
September 28, 2010
A startup called SeqCentral has stated its goal to democratize science by using the cloud for genetic alignment of DNA sequences, which is a critical stage during the process of genetic research. Read more…
As Federal agencies navigate an increasingly complex and data-driven world, learning how to get the most out of high-performance computing (HPC), artificial intelligence (AI), and machine learning (ML) technologies is imperative to their mission. These technologies can significantly improve efficiency and effectiveness and drive innovation to serve citizens' needs better. Implementing HPC and AI solutions in government can bring challenges and pain points like fragmented datasets, computational hurdles when training ML models, and ethical implications of AI-driven decision-making. Still, CTG Federal, Dell Technologies, and NVIDIA unite to unlock new possibilities and seamlessly integrate HPC capabilities into existing enterprise architectures. This integration empowers organizations to glean actionable insights, improve decision-making, and gain a competitive edge across various domains, from supply chain optimization to financial modeling and beyond.
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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