February 06, 2013
A team of Croatian researchers published a paper in the January 2013 edition of Scientific-professional Journal of Technical Faculties of University in Osijek examining the present state of high-performance computing in the cloud with an emphasis on currently-available solutions.
The authors provide a review of the key benefits of cloud: namely better resource utilization, efficient charge back mechanisms, on-demand provisioning and dynamic reallocation, and the potential to resolve peak workload demands (aka bursting).
In spite of these many advantages, however, HPC cloud still faces an uphill battle as it seeks to address technical and cultural barriers. Accordingly, the majority of HPC solutions continue to be the traditional, earth-bound variety. The biggest challenge is I/O-related. The slow network speeds and commodity interconnects that characterize most clouds present significant bottlenecks to data-intensive applications. But there are additional contributing factors underlying the slow rate of adoption, the authors observe. Virtualization, for example, adds a layer of complexity that is an anathema to the most latency-sensitive HPC workloads, while a growing reliance on co-processors presents its own set of challenges for HPC scaling.
HPC vendors are in the interesting position of being able to either support or retard the HPC cloud model. When it comes to developing cloud-friendly software models, the major ISVs have dragged their feet, not wanting to risk the cannibalization of proven income streams. But there are signs of momentum with most vendors now offering some level of cloud offering.
The researchers make the case that HPC vendors have indeed begun offering "fully functional HPC cloud solution[s]." In light of this, they recommend a set of helpful questions for would-be adopters:
The paper includes an overview of several current first, second and third-tier HPC cloud solutions.
The authors hope that their work will act as a "helpful compass for someone trying to shift from standard HPC to large computations in cloud environments."
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.