The high performance networking interconnect landscape is in transition. InfiniBand and Intel Omni-Path will compete for the performance crown, while Ethernet will remain the ubiquitous standard for commercially oriented systems.
Object stores represent a simpler, more scalable solution and one that is easily accessed over standard web-based protocols. To learn more about Object Stores download this guide.
For this report, DDN performed a number of experimental benchmarks to attain optimal IO rates for Paradigm Echos application workloads. It present results from IO intensive Echos micro-benchmarks to illustrate the DDN GRIDScaler performance benefits and provide some detail to aid optimal job packing in 40G Ethernet clusters. To find out the results download this guide.
A parallel file system offers several advantages over a single direct attached file system. By using fast, scalable, external disk systems with massively parallel access to data, researchers can perform analysis against much larger datasets than they can by batching large datasets through memory. To Learn More about the Parallel File Systems download this guide
“With three primary network technology options widely available, each with advantages and disadvantages in specific workload scenarios, the choice of solution partner that can deliver the full range of choices together with the expertise and support to match technology solution to business requirement becomes paramount.”
With the advent of heterogeneous computing systems that combine both main CPUs and connected processors that can ingest and process tremendous amounts of data and run complex algorithms, artificial intelligence (AI) technologies are beginning to take hold in a variety of industries. Massive datasets can now be used to drive innovation in industries such as autonomous driving systems, controlling power grids and combining data to arrive at a profitable decision, for example. Read how AI can now be used in various industries using the latest hardware and software.
To achieve high performance, modern computer systems rely on two basic methodologies to scale resources. A scale-up design that allows multiple cores to share a large global pool of memory and a scale-out design design that distributes data sets across the memory on separate host systems in a computing cluster. To learn more about In-Memory computing download this guide from IHPC and SGI.
SGI’s Data Management Framework (DMF) software – when used within personalized medicine applications – provides a large-scale, storage virtualization and tiered data management platform specifically engineered to administer the billions of files and petabytes of structured and unstructured fixed content generated by highly scalable and extremely dynamic life sciences applications.
In life sciences, perhaps more than any other HPC discipline, simplicity is key. The SGI solution meets this requirement by delivering a single system that scales to huge capabilities by unifying compute, memory, and storage. Researchers and scientists in personalized medicine (and most life sciences) are typically not computer science experts and want a simple development and usage model that enables them to focus on their research and projects.
FPGAs will become increasing important for organizations that have a wide range of applications that can benefit from performance increases. Rather than a brute force method to increasing performance in a data center by purchasing and maintaining racks of hardware and associated costs, FPGAs may be able to equal and exceed the performance of additional servers, while reducing costs as well.