September 24th, 2018 by intel
What’s New: Intel today announced details on the expansion of its portfolio of 100G silicon photonics transceivers beyond the data center and into the network edge. At the European Conference on Optical Communication (ECOC) in Rome, Intel unveiled specifics on new silicon photonics products that are optimized to accelerate the movement of massive amounts of data being generated by new 5G use cases and Internet of Things (IoT) applications. The latest 100G silicon photonics transceivers are optimized to meet the bandwidth requirements of next-generation communications infrastructure while withstanding harsh environmental conditions.
Intel Corporation’s portfolio of 100G silicon photonics transceivers are optimized to meet the bandwidth requirements of next-generation communications infrastructure while withstanding harsh environmental conditions. (Credit: Intel Corporation)
“Our hyperscale cloud customers are currently using Intel’s 100G silicon photonics transceivers to deliver high-performance data center infrastructure at scale. By extending this technology outside the data center and into 5G infrastructure at the edge of the network, we can provide the same benefits to communications service providers while supporting 5G fronthaul bandwidth needs.”
– Dr. Hong Hou, vice president and general manager of Intel’s Silicon Photonics Product Division
Why It’s Important: In the data-centric era, the ability to move, store and process data is paramount. Intel’s 100G silicon photonics solutions deliver tremendous value by offering fast, reliable and cost-effective connectivity. The industry’s move to 5G, along with a ramp in existing network traffic such as video streaming, is straining existing communications infrastructure that must support an expanded spectrum range including mmWaves, massive MIMO and network densification. Intel’s latest 100G silicon photonics transceivers meet the bandwidth demands of 5G wireless fronthaul applications. These transceivers are designed to meet the harsh outdoor conditions of cellular towers with the capability to support optical transport to the nearest baseband unit or central office (up to 10 km).
Read the rest of Intel Targets 5G Infrastructure with Latest Silicon Photonics Technology
August 8th, 2018 by intel
Intel outlines vision for reimagining memory and storage with Optane + QLC. Intel is reimagining the memory-and-storage market and igniting a new era of computing with a combination of two unique memory technologies in memory and storage solutions no one in the industry currently offers: Intel® Optane™ and Intel® QLC 3D NAND.
Intel is reimagining the memory-and-storage market and igniting a new era of computing with the combination of Intel Optane and Intel QLC 3D NAND technologies. (Credit: Peter Belanger Photography)
“Intel Optane and 3D NAND technologies ensure computer and storage architects and developers can access vital data where and when they need it. The two technologies bridge the wide gap that exists between data that’s being worked on and data that’s waiting to be accessed.”
– Rob Crooke, senior vice president and general manager of the Non-Volatile Memory Solutions Group at Intel
Why It’s Important: The combination of Intel Optane and Intel QLC 3D NAND technologies allows customers to accelerate the speed of their most frequently accessed data, while utilizing the value flash technology delivers over HDDs for massive capacity storage. Intel’s aim is to break bottlenecks and deliver better solutions to unleash the value of data.
How It’s Used: Optane has already had an impact throughout the world. Here are a few examples:
- Intel Optane SSDs integrated into IBM Cloud’s bare metal servers have enabled up to 7.5 times improvement — especially for applications that have high write-intensive operations.
- Using Intel Optane Technology, the University of Pisa has reduced MRI scan times from 42 minutes to 4 minutes.
- Intel Optane has enabled IFLYTEK, a Chinese information technology company, to enable faster voice and facial recognition services.
Intel’s QLC 3D NAND products announced today at Flash Memory Summit deliver new memory and storage solutions: Tencent, employing the new QLC PCIe Intel® SSD D5-P4320 in an initial production environment, increased by 10 times the number of customers served on a per-system basis.
Read the rest of Intel Poised to Shape the Future of Memory and Storage with Optane + QLC
What’s New: The Smithsonian American Art Museum* (SAAM) exhibition, “No Spectators: The Art of Burning Man,” is now available in virtual reality (VR) through Sansar*, the premier destination for social VR. Powered by Intel technology, this recently announced partnership will make iconic artwork more accessible and interactive through virtual reality.
Marco Cochrane, “Truth is Beauty,” 2017. Powered by Intel technology, the Smithsonian American Art Museum?s exhibition, “No Spectators: The Art of Burning Man,” was digitally captured and processed into an immersive virtual reality experience, now available via the Sansar platform. (Credit: Smithsonian Institution)
“Intel empowers the creator to take their work to the next level. Technology has the potential to achieve new goals and ambitions for museums and galleries. Immersive technologies, like virtual reality, unlock new and exciting ways to experience art and exhibits. Fans can now check out “No Spectators” from their own home. Without Intel’s high-performance processors, these experiences would not be possible.”
– Raj Puran, director of immersive technology business development at Intel Corporation
Read the rest of Explore Smithsonian American Art Museum Exhibition, Now Live in Virtual Reality
Intel’s partnership with the China Foundation for Cultural Heritage Conservation (CFCHC) to protect and preserve the Jiankou section of the Great Wall of China is underway. And experts from Wuhan University LIESMARS have been added to the project, leveraging Intel technologies to preserve the wall more efficiently and safely than before.
An Intel Falcon 8+ drone is prepared for aerial inspection of the Great Wall of China. In 2018, Intel Corporation announced a partnership with the China Foundation for Cultural Heritage Conservation to protect and restore the Great Wall of China. (Credit: Intel Corporation
This is the next step in Intel’s recently announced commitment to inspect and preserve the Jiankou section of the Great Wall. By incorporating advanced technologies into this partnership, Intel is giving conservationists new tools to protect history and help preserve one of the great architectural wonders of the world.
Read the rest of Intel Technology Aids in Preserving the Great Wall of China
What’s New: Today at Baidu* Create in Beijing, Intel Vice President Gadi Singer shared a series of collaborations with Baidu on artificial intelligence (AI), including powering Baidu’s Xeye* a new AI retail camera with Intel® Movidius™ vision processing units (VPUs); highlighting Baidu’s plans to offer workload acceleration as a service using Intel® FPGAs; and optimizing PaddlePaddle*, Baidu’s deep learning framework for Intel® Xeon® Scalable processors.
“From enabling in-device intelligence, to providing data center scale on Intel Xeon Scalable processors, to accelerating workloads with Intel FPGAs, to making it simpler for PaddlePaddle developers to code across platforms, Baidu is taking advantage of Intel’s products and expertise to bring its latest AI advancements to life.”
–Gadi Singer, vice president and architecture general manager, Artificial Intelligence Products Group, Intel
How the Camera Works: Baidu’s Xeye camera uses Intel® Movidius™ Myriad™ 2 VPUs to deliver low-power, high-performance visual intelligence for retailers. Thanks to Intel’s purpose-built VPU solutions coupled with Baidu’s advanced machine learning algorithms, the camera can analyze objects and gestures, while also detecting people to provide personalized shopping experiences in retail settings.
Read the rest of Intel AI at Baidu Create: AI Camera, FPGA-based Acceleration and Xeon Scalable Optimizations for Deep Learning
Intel and Ecosystem Partners Introduce New Solutions to Secure Data in Emerging Technologies
By Rick Echevarria
The future of a trusted and secure computing environment hinges on our collective ability to deliver solutions that improve the performance across a variety of workloads, while also optimizing security.
This week, at Cyber Week in Israel, I am joined by partners, customers, and cybersecurity industry and policy leaders from across the globe. Intel is committed to providing silicon-based security solutions that address the most pressing issues. There are three key themes at the conference, highlighting the challenges and opportunities facing our industry.
Emerging Workloads Deliver More Data to Analyze and Secure
Incoming data is increasingly difficult to effectively leverage without the computing power to process and learn from its growing volume and complexity. Machine learning (ML) algorithms, and other artificial intelligence (AI) applications and capabilities, have achieved remarkable results and are being extensively used in different domains. ML algorithms often require access to sensitive data, especially as the focus on data privacy increases around the world. Limiting access to the right data may limit the outcomes that can be achieved with the use of AI. In the case of blockchain, the security and privacy of data join transaction scalability as key technical considerations.
Read the rest of Intel Advances Silicon-Based Security for AI and Blockchain Workloads
Intel researchers are taking new steps toward quantum computers by testing a tiny new “spin qubit” chip. The new chip was created in Intel’s D1D Fab in Oregon using the same silicon manufacturing techniques that the company has perfected for creating billions of traditional computer chips. Smaller than a pencil’s eraser, it is the tiniest quantum computing chip Intel has made.
A 2018 photo shows Intel’s new quantum computing chip balanced on a pencil eraser. Researchers started testing this “spin qubit chip” at the extremely low temperatures necessary for quantum computing: about 460 degrees below zero Fahrenheit. Intel projects that qubit-based quantum computers, which operate based on the behaviors of single electrons, could someday be more powerful than today’s supercomputers. (Credit: Walden Kirsch/Intel Corporation)
The new spin qubit chip runs at the extremely low temperatures required for quantum computing: roughly 460 degrees below zero Fahrenheit – 250 times colder than space.
The spin qubit chip does not contain transistors – the on/off switches that form the basis of today’s computing devices – but qubits (short for “quantum bits”) that can hold a single electron. The behavior of that single electron, which can be in multiple spin states simultaneously, offers vastly greater computing power than today’s transistors, and is the basis of quantum computing.
The zigzag lines in the photo are printed wires connecting the chip’s qubits to the outside world.
One feature of Intel’s tiny new spin qubit chip is especially promising. Its qubits are extraordinarily small – about 50 nanometers across and visible only under an electron microscope. About 1,500 qubits could fit across the diameter of a single human hair.
This means the design for new Intel spin qubit chip could be dramatically scaled up. Future quantum computers will contain thousands or even millions of qubits — and will be vastly more powerful than today’s fastest supercomputers.
Intel Optane DC Persistent Memory Represents a New Class of Memory and Storage Technology Architected to Extract Further Value from Data
By Lisa Spelman
We’ve all heard about escalating mountains of data – and yes, there is a tremendous amount of data generated daily that must be stored, secured and organized. More interesting than the amount of data is the value it represents. Value that comes from analysis and the resulting insights. Data may store the next great business opportunity, societal advancement or scientific discovery.
While we’ve made great progress as an industry in providing the infrastructure, tools and best practices to drive this analysis, limitations are also emerging. Not only is the volume and variety of data growing, but the velocity of desired insights is accelerating. To really tap into all of this data, we must remove the bottlenecks that restrict its flow and readiness for processing.
Today, we’re sharing the first in-depth look at how Intel is reimagining the memory and storage hierarchy for application developers and data solution providers with the upcoming introduction of Intel® Optane™ DC persistent memory. Intel Optane DC persistent memory represents a new class of memory and storage technology architected specifically for data center usage. One that we believe fundamentally breaks through some of the constricting methods for using data that have governed computing for more than 50 years.
Read the rest of Reimagining the Data Center Memory and Storage Hierarchy
Intel’s Gadi Singer believes his most important challenge is his latest: using artificial intelligence (AI) to reshape scientific exploration.
In a Q&A timed with the first Intel AI DevCon event, the
Gadi Singer, vice president and architecture general manager for the Artificial Intelligence Products Group at Intel, uses artificial intelligence to reshape scientific exploration. Before his role with AI, the 35-year Intel veteran helped create the first Pentium processor; led development of the first Xeon processors and the first Atom processor; and oversaw architecture for generations of the Intel Core processors. (Photo Credit: Walden Kirsch/Intel Corporation)
Intel vice president and architecture general manager for its Artificial Intelligence Products Group discussed his role at the intersection of science — computing’s most demanding customer — and AI, how scientists should approach AI and why it is the most dynamic and exciting opportunity he has faced.
Q. How is AI changing science?
Scientific exploration is going through a transition that, in the last 100 years, might only be compared to what happened in the ‘50s and ‘60s, moving to data and large data systems. In the ‘60s, the amount of data being gathered was so large that the frontrunners were not those with the finest instruments, but rather those able to analyze the data that was gathered in any scientific area, whether it was climate, seismology, biology, pharmaceuticals, the exploration of new medicine, and so on.
Today, the data has gone to levels far exceeding the abilities of people to ask particular queries or look for particular insights. The combination of this data deluge with modern computing and deep learning techniques is providing new and many times more disruptive capabilities.
Read the rest of How is Artificial Intelligence Changing Science?
What’s New: Intel collaborates with Novartis* on the use of deep neural networks (DNN) to accelerate high content screening – a key element of early drug discovery. The collaboration team cut time to train image analysis models from 11 hours to 31 minutes – an improvement of greater than 20 times1.
Collaboration team members from Novartis and Intel used eight CPU-based servers, a high-speed fabric interconnect and optimized TensorFlow to achieve the improvement in time needed to process a dataset of 10K images.
Why It’s Important: High content screening of cellular phenotypes is a fundamental tool supporting early drug discovery. The term “high content” signifies the rich set of thousands of pre-defined features (such as size, shape, texture) that are extracted from images using classical image-processing techniques. High content screening allows analysis of microscopic images to study the effects of thousands of genetic or chemical treatments on different cell cultures.
The promise of deep learning is that relevant image features that can distinguish one treatment from another are “automatically” learned from the data. By applying deep neural network acceleration, biologists and data scientists at Intel and Novartis hope to speed up the analysis of high content imaging screens. In this joint work, the team is focusing on whole microscopy images as opposed to using a separate process to identify each cell in an image first. Whole microscopy images can be much larger than those typically found in deep learning datasets. For example, the images used in this evaluation are more than 26 times larger than images typically used from the well-known ImageNet* dataset of animals, objects and scenes.
Read the rest of Using Deep Neural Network Acceleration for Image Analysis in Drug Discovery