Next week, PC vendors will start rolling out patches that fix a severe vulnerability found in certain Intel-based business systems, including laptops, making them easier to hack. Intel on Friday released a new notice urging clients to take steps to secure their systems. The chipmaker has also released a downloadable tool that can help IT administrators and users discover whether a machine they own has the vulnerability. In addition, vendors including Fujitsu, HP, and Lenovo have released lists showing which products are affected and when the patches will roll out. The products include laptops from Lenovo's ThinkPad line and HP's EliteBook series, along with servers, and desktops. Some of the patches are slated to come in June. Computers running enterprise management features found in Intel-based firmware from the past eight years will have the bug. Specifically, the vulnerability resides in past versions of Intel Active Management Technology, Intel Small Business Technology, and Intel Standard Manageability. Fortunately, the vulnerability can only be exploited if these features have been enabled, according to security firm Embedi, which uncovered the bug. Read more at http://www.pcworld.com/article/3195029/security/patch-to-fix-intel-based-pcs-with-enterprise-bug-rolls-out-next-week.html

One of the most popular passwords in 2016 was "qwertyuiop," even though most password meters will tell you how weak that is. The problem is no existing meters offer any good advice to make it better—until now. Researchers from Carnegie Mellon University and the University of Chicago have just unveiled a new, state-of-the-art password meter that offers real-time feedback and advice to help people create better passwords. To evaluate its performance, the team conducted an online study in which they asked 4,509 people to use it to create a password. "Instead of just having a meter say, 'Your password is bad,' we thought it would be useful for the meter to say, 'Here's why it's bad and here's how you could do better,'" says CyLab Security and Privacy Institute faculty Nicolas Christin, a professor in the department of Engineering and Public Policy and the Institute for Software Research at Carnegie Mellon, and a co-author of the study. The study will be presented at this week's CHI 2017 conference in Denver, Colorado, where it will also receive a "Best Paper Award." This data-driven feedback is presented in real-time, as a user is typing their password out letter-by-letter. The team has open-sourced their meter on GitHub. Read more at https://phys.org/news/2017-05-unveil-password-meter-users-passwords.html

Today Infervision introduced its innovative, deep learning solution to help radiologists identify suspicious lesions and nodules in lung cancer patients faster than ever before. The Infervision AI platform is the world’s first to reshape the workflow of radiologists and it is already showing dramatic results at several top hospitals in China. Infervision’s AI-aided CT diagnosis, with its high-performance parallel computing power, effectively learns the core characteristics of lung cancer and efficiently detects suspected cancer features in different CT image sequences, helping with early diagnosis and consequently early treatment. The technology is also used to assist in X-ray diagnosis and has achieved extremely high accuracy so that it is close to that of a deputy chief physician in the diagnosis of cardiothoracic diseases at one of the top Chinese hospitals where the software is now in use. For the past six months, the technology has been in use at several top hospitals in China, a country experiencing hundreds of thousands of new lung cancer patients annually, while it has too few radiologists. After rigorous testing and integrating the software with the standard PACS (picture archiving and communication system), Infervision’s technology is proving to be extremely effective and is enhancing the work of Chinese doctors by acting as a second pair of eyes. Read more at http://insidehpc.com/2017/05/ai-technology-china-helps-radiologists-detect-lung-cancer/

“Build it and they will come” is one way to approach building a supercomputer, but it’s not what the National Center for Supercomputing Applications (NCSA) did with Blue Waters, the largest leadership-class National Science Foundation supercomputer. Prior to the system going online in April 2013, Blue Waters staff worked with more than 20 science teams to determine a unique, balanced hardware configuration—a process now known as co-design. Three years later, a sample of 31 science teams that have used Blue Waters were surveyed and interviewed as part of a report meant to judge the effectiveness and productivity of this unique system—housed at NCSA’s home institution, the University of Illinois at Urbana-Champaign. Using information gathered in the surveys, the report’s authors at International Data Corporation’s HPC division (now known as Hyperion Research) ranked the impact of each team’s findings into an “innovation index”—using a methodology they developed to analyze the effectiveness of 700-plus scientific projects, including international HPC projects. The Hyperion Research analysts noted in the report that “NCSA did an unusually thorough job of preparing [science teams] for Blue Waters.” Read more at https://www.hpcwire.com/off-the-wire/ncsa-highlights-scientific-impacts-three-years-blue-waters/

Today SC17 announced that 16 teams will take part in the Student Cluster Competition. Hailing from across the U.S., as well as Asia and Europe, the student teams will race to build HPC clusters and run a full suite of applications in the space of just a few days. The Student Cluster Competition is a high energy event featuring young supercomputing talent from around the world competing to build and operate powerful cluster computers. Created as an opportunity to showcase student expertise in a friendly yet spirited competition, the SCC aims to introduce the next generation of students to the high-performance computing community. The number of teams selected for SC17 is the highest since the first event was held at SC07 in Reno, and the 19 reviewers sifted through 20 team applications, also the highest number to date. The SC17 competition will also mark the first time that the winners of the world’s top three student cluster competitions will meet: SC16 winner University of Science and Technology of China; Tsinghua University of China, winner of the ASC17 Student Supercomputer Challenge; and the winner of the upcoming ISC Student Cluster Competition to be held in June. Learn more at http://insidehpc.com/2017/05/sixteen-teams-compete-sc17-student-cluster-competition/

Do you, or someone you know, know how to program computers? NASA has a challenging assignment for you. NASA’s aeronautical innovators are sponsoring a competition to reward qualified contenders who can manipulate the agency’s FUN3D design software so it runs ten to 10,000 times faster on the Pleiades supercomputer without any decrease in accuracy. The competition is called the High Performance Fast Computing Challenge (HPFCC). “This is the ultimate ‘geek’ dream assignment,” said Doug Rohn, director of NASA’s Transformative Aeronautics Concepts Program (TACP). “Helping NASA speed up its software to help advance our aviation research is a win-win for all.” NASA’s aviation research is based on what is often described as a three-legged stool. One leg sees initial designs tested with computational fluid dynamics, or CFD, which relies on a supercomputer for numerical analysis and data structures to solve and analyze problems. Learn more at https://www.hpcwire.com/off-the-wire/nasa-issues-challenge-speed-fun3d-supercomputer-code/

Some scientists dream about big data. The dream bridges two divided realms. One realm holds lofty peaks of number-crunching scientific computation. Endless waves of big data analysis line the other realm. A deep chasm separates the two. Discoveries await those who cross these estranged lands. Unfortunately, data cannot move seamlessly between Hadoop (HDFS) and parallel file systems (PFS). Scientists who want to take advantage of the big data analytics available on Hadoop must copy data from parallel file systems. That can slow workflows to a crawl, especially those with terabytes of data. Computer Scientists working in Xian-He Sun's group are bridging the file system gap with a cross-platform Hadoop reader called PortHadoop, short for portable Hadoop. "PortHadoop, the system we developed, moves the data directly from the parallel file system to Hadoop's memory instead of copying from disk to disk," said Xian-He Sun, Distinguished Professor of Computer Science at the Illinois Institute of Technology. Sun's PortHadoop research was funded by the National Science Foundation and the NASA Advanced Information Systems Technology Program (AIST). The concept of 'virtual blocks' helps bridge the two systems by mapping data from parallel file systems directly into Hadoop memory, creating a virtual HDFS environment. These 'virtual blocks' reside in the centralized namespace in HDFS NameNode. The HDFS MapReduce application cannot see the 'virtual blocks'; a map task triggers the MPI file read procedure and fetches the data from the remote PFS before its Mapper function processes its data. In other words, a dexterous slight-of-hand from PortHadoop tricks the HDFS to skip the costly I/O operations and data replications it usually expects.Learn more at https://www.tacc.utexas.edu/-/reaching-for-the-stormy-cloud-with-chameleon

The San Diego Supercomputer Center (SDSC) at the University of California San Diego has been granted a supplemental award from the National Science Foundation (NSF) to double the number of graphic processing units, or GPUs, on its petascale-level Comet supercomputer in direct response to growing demand for GPU computing across a wide range of research domains. Under the supplemental NSF award, valued at just over $900,000, SDSC is expanding the high-performance computing resource with the addition of 36 GPU nodes, each with four NVIDIA P100s, for a total of 144 GPUs. This will double the number of GPUs on Comet from the current 144 to 288. The nodes are being provided by Dell, the vendor and co-design partner for Comet. They are expected to be in production by early July. The expansion will make Comet the largest provider of GPU resources available to the NSF-funded Extreme Science and Engineering Discovery Environment (XSEDE), a national partnership of institutions that provides academic researchers with the most advanced collection of digital resources and services in the world. Prior to this award, the NSF granted SDSC a total of $24 million to develop and operate Comet, which went into production in mid-2015. Once used primarily for video game display graphics, today’s much more powerful GPUs have been developed that have more accuracy, speed, and accessible memory for more scientific applications that range from phylogenetics and molecular dynamics to creating some the most detailed seismic simulations ever made to better predict ground motions to save lives and minimize property damage. Learn more at http://www.sdsc.edu/News%20Items/PR20170502_Comet_GPU.html

Today MapD Technologies released the MapD Core database to the open source community under the Apache 2 license, seeding a new generation of data applications. “Open source is sparking innovation for data science and analytics developers,” said Greg Papadopoulos, venture partner at New Enterprise Associates (NEA). “An open-source GPU-powered SQL database will make entirely new applications possible, especially in machine learning where GPUs have had such an enormous impact. We’re incredibly proud to partner with the MapD team as they take this pivotal step.” MapD pioneered the use of graphics processing units (GPUs) to analyze multi-billion-row datasets in milliseconds, orders-of-magnitude faster than traditional CPU-based systems. By open sourcing the MapD Core database and associated visualization libraries, MapD is making the world’s fastest analytics platform available to everyone. MapD has also released a free Community Edition of its software for non-commercial development and academic use. The MapD Community Edition includes the MapD Core database and MapD Immerse visual analytics client.Learn more at http://insidehpc.com/2017/05/mapd-open-sources-high-speed-gpu-powered-database/

The much-anticipated unification of Intel’s Xeon E3, E5 and E7 product lines is upon us. Starting with the upcoming “Skylake” datacenter chips, all Xeons will now fall under the new Xeon Scalable Processor (SP) family. As a result, the Xeon EP, and EX suffixes are being consolidated into a single SP designation. However, under the new structure, Intel has come up with four processor levels: Platinum, Gold, Silver, and Bronze. It’s anticipated that the old E3 (single-socket), E5 (dual-socket) and E7 (quad-socket/multi-socket) will map to the Silver, Gold and Platinum levels, respectively, but since four levels need to be filled, it’s likely to get a bit more nuanced than that. In any case, Intel is using the announcement of the new family to tee up the Skylake silicon, which according to an editorial penned by Intel VP and GM Lisa Spelman, represents “the biggest set of data center platform advancements in this decade.” Skylake will include a number of integrated “performance accelerators,” namely the 512-bit Advanced Vector Extensions (AVX-512), QuickAssist Technology (QAT), and the Volume Management Device (VMD). Not all Skylake SP chips will include all these accelerators. Rather, they will be distributed across the various levels and individual SKUs based on their anticipated target audience. Learn more at https://www.top500.org/news/intel-consolidates-xeon-product-lines/

GPU Technology Conference – Super Micro Computer, Inc., a global leader in compute, storage and networking technologies including green computing, will exhibit new GPU-based servers at the GPU Technology Conference (GTC) from May 8 to 11 at the San Jose Convention Center, Booth #111. Optimized applications for Supermicro GPU supercomputing systems include Machine Learning, Artificial Intelligence, HPC, Cloud and Virtualized graphics, and Hyperscale Workloads. Supermicro will have on display the SYS-1028GQ-TXRT and SYS-4028GR-TXRT with support for four and eight NVIDIA Tesla P100 SXM 2.0 modules, respectively, both featuring NVIDIA NVLink™ interconnect technology. Supermicro will also be displaying its multi-node GPU solutions and high-performance workstations with support for 4 PCIe 3.0 x16 slots. NVIDIA’s GPU computing platform provides a dramatic boost in application throughput for HPC, advanced analytics and AI workloads,” said Paresh Kharya, Tesla Product Management Lead at NVIDIA. With our Tesla data center GPUs, Supermicro’s new high-density servers offer customers high performance and superior efficiency to address their most demanding computing challenges.” Learn more at https://www.hpcwire.com/off-the-wire/supermicro-systems-deliver-170-tflops-fp16-peak-performance-ai-gtc/