Be Careful What You Wish For Steve Conway, IDC Research VP, HPC In 1995, the global market for high performance computing (HPC) servers, a.k.a. supercomputers, was worth about $2 billion. By 2010, that figure nearly quintupled to $9.5 billion, thanks to the rise of HPC clusters based on commercial, off-the-shelf (COTS) technologies.
Everyone’s a winner in the race for a common application language that can support both x86 and massively parallel hardware Rob Farber Commercial and research projects must now have parallel applications to compete for customer and research dollars. This translates into pressure on software development efforts that have to control costs while supporting a range of rapidly evolving parallel hardware platforms. What is needed is a common programming language that developers can use to create parallel applications with a single source tree that can run on current and future parallel hardware.
While it is common for users in various laboratories and industries to feel that their processes are unique, in many ways, they all have common needs. Similarly, in many respects, all laboratory information management systems (LIMS) are alike, or at least they should be. All must perform basic functions, such as track the users entering data, track the samples arriving at the laboratory and their processing through it...
Before you decide to rock the boat, several key decision-making steps can help to ensure a smooth and successful upgrade Peter J. Boogaard The upside of upgrading the IT infrastructure will give many organizations the ability to eliminate barriers to enable cross-functional collaboration between research, development, quality assurance and manufacturing. Standardizing workflows and operating procedures and applying best industry practices throughout operations also are key drivers. Quick advantage occurs when the implementation is fast and when it results in strategic value. This article will highlight key decision-making steps to be considered when upgrading your software.
For those new to this software, perhaps a little background is in order. Maple is mathematical software that is constantly being improved as to breadth of the calculation routines, optimality of the algorithms, speed of computation, and ease-of-use. The last is one of the most useful features, as the new user can quickly come up to speed by testing the menu items, going through the tutorials and reading the pertinent sections of the manuals
Using what you have in a smarter way Dan Joe Barry, Napatech Web Exclusive If you like theory, then you’ll be interested to know that many are predicting that data center traffic is set to sharply increase. As cloud computing centralizes, more computing resources and more devices, such as mobile phones, tablets and TVs, are being used to exchange data.
Avoiding the consequences of cutting corners Christopher Bauer, Ph.D. Web Exclusive Times are tough in business right now, certainly including laboratory informatics, and any sane business person is trying to cut corners in any way possible. Scaling back on your attention to ethics, however, can have catastrophic consequences. Between the possible fines, legal fees and reputational damage to you and your company, you could lose anything from thousands to millions of dollars as well as your career or business. No matter how tough the times are, that kind of risk is simply not worth taking. Unfortunately, though, tough times can easily make it seem worth trying to cut ethical corners if it looks like there might be some financial gain from it.
Solving the problems of “big” data growth Will McGrath Web Exclusive The explosion of data growth created by next-gen instruments has caused tremendous challenges in handling and storing those files. While growth in structured and semi-structured data — like e-mail and databases — continues to grow, it is really unstructured “big” data growth that is causing the biggest problems. This is true in verticals like oil and gas with upstream seismic and interpretation applications or in life sciences with a number of newer instruments being introduced for electron microscopy, high content screening / high throughput screening and flow cytometry — or especially, next generation sequencing (NGS).
Intelligent use remains the best way to exploit speed and maintain the highest possible ROI Rob Farber Solid-state storage is revolutionizing computer storage. Unlike the currently ubiquitous rotating media disk drives, solid-state disk drives have no moving parts to waste power or delay data accesses. The fastest PCIe-based solid-state devices can perform over a million random disk accesses per second, while the fastest rotating media disk drives can deliver around 200 random disk accesses per second
How the University of Washington scaled up with a LIMS Mike Sanders Web Exclusive When the University of Washington (UW) received a $23 million portion of a $64 million grant for the Large-Scale Exome Sequencing Project from the National Heart Lung and Blood Institute (NHLBI), investigators knew the clock was ticking. Grants generally have a limited shelf-life and this was no exception. The UW’s Northwest Genomics Center would need to sequence a total of 4,000 exomes over two years — an ambitious goal in a tight timeframe. Moreover, DNA would come from large cohort studies such as the Framingham Heart Study and the Women’s Health Initiative.
Joseph Yaworski Web Exclusive High performance computing applications require a tuned and efficient performance from the CPU, interconnect, MPI and communication library to achieve optimal performance. Conventional wisdom would have you believe that the host channel adapters (HCAs) with offload capability, where processing power for running the communication library is on a card, would require less CPU utilization than HCAs using an on-load method, where the communication library is run on the host CPU, thus, allowing more CPU cycles for applications
Enabling Collaboration Bennett Lass Ph.D. Web Exclusive This is the fourth entry in a series on best practices in Electronic Lab Notebook (ELN) implementation. The first article identified five core areas which need to be managed to ensure a successful ELN deployment. This article discusses the third core area: collaboration.
Technologies are evolving to simplify integration and reduce long-term risk Michael H. Elliott Over the years, the desire to solve the myriad of data management problems in the laboratory has led to a plethora of point solutions. Not counting the vast number of instrument data management systems, it is not uncommon that a typical scientist has over 10 different systems to navigate. Despite all the sophisticated capabilities provided by these tools, over 20 percent of the average scientist’s time is spent on non-value-added data aggregation, transcription, formatting and manual documentation.
It’s always refreshing to see the latest version of an old friend and, in this case, delve into capabilities that go far beyond the simple algebra and calculus where the editor usually turns to this software (also to shed light on a biological process). Mathematica has expanded into so many areas, that it long ago ceased to be software that merely does math.
While exciting, innovations in next-generation genome sequencing require painstaking development William L. Weaver, Ph.D. In 1898, Samuel P. Langley received a $70,000 grant from the United States War Department and the Smithsonian Institution to develop a piloted airplane. Langley invented a series of successful unmanned powered aircraft that were launched by a catapult system mounted on the roof of a houseboat anchored in the Potomac river — a system that would later serve as the basis for modern aircraft carriers.