Showing posts with label ARM Hardwares. Show all posts
Parties to work together to accelerate virtualized BBUs based on General-Purpose Processors
SAN JOSE, CA December 8th, 2016 - Today, Cavium, Inc. (NASDAQ: CAVM), a leading provider of semiconductor products that enable intelligent processing for Enterprise, Telco, MSP and cloud data centers, announced an agreement with China Unicom to accelerate the design and development of Virtualized BBU and provide a path for 5G adoption. The collaboration will focus on commercializing vBBU systems using general purpose hardware based on Cavium’s ThunderX® workload optimized data server processors which are built on ARM architecture. In addition, Cavium has joined the China Unicom CORD Industry Alliance and will drive adoption of open source architecture and technologies in China together with China Unicom.
China Unicom and Cavium will work together on new innovative fronthaul solutions, system architecture and vBBU performance and deployment. This collaboration allows Cavium to align with China Unicom’s commercial networks technology development and innovation, research feasibility of Next Generation Virtualized Wireless Access Network, perform lab and field testing, evaluate results, drive deployment of developed technologies into commercial network, carry out lab and field performance test and assessment, accelerate pilot and application of new technical innovations in real-world networks.
“We are very pleased to collaborate with China Unicom in this critical area. As network capacity continues to be stretched and the user demands continue to grow the industry is faced with significant challenges which cannot be solved by traditional means,” said Raj Singh General Manager of the Wireless Broadband Group at Cavium. “The use of advanced general purpose hardware such as Cavium’s ThunderX workload optimized data severs allows us to provide a highly scalable virtualized solution for these requirements.”
“Virtualized network based on general purpose hardware and open source technologies represents the overall direction for future network changes. China Unicom partners with Cavium, a leader in virtualized BBU technology field, to drive R&D of virtualization products based on general purpose processors, thus laying a solid foundation for building new generation of network infrastructure,” said Dr. Tang Xiongyan, CTO of Network Technology Research Institute, China Unicom.
About Cavium
Cavium, Inc. (NASDAQ: CAVM), offers a broad portfolio of integrated, software compatible processors ranging in performance from 1Gbps to 100Gbps that enable secure, intelligent functionality in Enterprise, Data Center, Broadband/Consumer, Mobile and Service Provider Equipment, highly programmable switches which scale to 3.2Tbps and Ethernet and Fibre Channel adapters up to 100Gbps. Cavium processors are supported by ecosystem partners that provide operating systems, tools and application support, hardware reference designs and other products. Cavium is headquartered in San Jose, CA with design centers in California, Massachusetts, India, China and Taiwan. For more information, please visit: http://www.cavium.com.
Media Contact
Angel Atondo
Sr. Marketing Communications Manager
Telephone: +1 408-943-7417
Email: angel.atondo@cavium.com
Microsoft has been already in the news for the latest upcoming devices that are reported to be waiting in the pipeline to be released once 2017 sets in. And it’s back in the headline yet again but this time for a completely different reason. It is reported that Microsoft will be tying up with Qualcomm to enable the availability of Windows 10 desktops apps on ARM chipsets.
The news has come in that Windows 10 will be able to support ARM chipsets and the announcement has been made by the officials of both Microsoft and Qualcomm. This means that the desktop windows app will be available on the mobile devices like smartphones, laptops and tablets. And such compatible devices might come out “as early as next year” as the company officials have suggested.
It is also reported that the new Windows 10 which is going to support ARM chipsets from Qualcomm will be able to run desktop x86 Win32 apps besides the Universal Windows apps. This will surely make things much better particularly after the discontinuation of the Windows RT platform which did not feature any desktop apps. But it remains to be seen how well the apps perform because it is expected that the apps will still run better on the x86 chipsets made by Intel.
However, the latest developments have put under the scrutiny the relationship between Microsoft and Intel which many believe that might just have fallen out. But Terry Myerson, Executive Vice President of Microsoft, absolutely dismissed such possibilities. He has been quoted telling The Verge, “We’re working closer with Intel than we ever have before. The collaboration is better than ever before. It’s just the case where Qualcomm does have these chips with integrated connectivity and better idle power performance which enables new devices to get built.” Thus the speculations that the collaboration between Microsoft and Intel might come to an end in distant future should die down for the time being.
Regarding the availability of the PCs which would be coming out after such collaboration between Microsoft and Qualcomm, it is speculated that it might be very early in 2017. Qualcomm has been quoted saying that the Windows 10 based on Qualcomm Snapdragon processors are “expected to be available as early as next year.” so the tech enthusiasts across the world would be eager to watch out how these new devices perform when they are brought out in the market.
A video demonstrating Windows 10 and Adobe Photoshop running on an ARM-based device is reproduced below, with Qualcomm and Microsoft promising to launch the first units some time next year.
Packet’s not-so-secret weapon: energy-sipping bare-metal servers using ARM processors.
A
little-known startup is making a big bet that it can parlay new ARM chips, and
backing from a Japanese investment giant, to make its presence felt among the
cloud computing giants.
The
company, Packet, on Tuesday is launching new rentable “bare metal” computing
services based on the ARM v8 chip architecture from its data centers in New
Jersey, Northern California, Amsterdam, and Tokyo. Customers can set up and
launch these resources within minutes, Packet said
The
move is unusual because ARM chips are not commonly found in the servers that
power corporate data centers or public cloud computer services, such as those
sold by Amazon AMZN -1.47% Web Services. They do, however, dominate the
smartphone market—scratch an Apple AAPL
-1.87% iPhone (God forbid) and you’ll
see an ARM chip. And many techies see ARM’s energy-efficient design as an
interesting option for servers going forward.
Bare
metal servers, unlike typical cloud-based servers, are not virtualized. That
means they can run certain jobs, like databases, faster than virtualized cloud
servers. IBM IBM -2.15% , Rackspace RAX 0.00%
and some other cloud companies already offer bare metal options for
rent.
New
York-based Packet, which disclosed $9.4 million in funding from Softbank in
September, aims to satisfy what it sees as a growing market for bare-metal
computing on demand. Softbank is a great ally for Packet, since it is buying
ARM Holdings for $32 billion. ARM Holdings is the U.K. company that controls
and licenses ARM processor designs to manufacturers.
Packet
CEO Zachary Smith acknowledges that this is a David and Goliath tale in many
ways. Intel chips dominate cloud computing services and equipment, as they do
inside corporate data centers. And Amazon Web Services and Microsoft MSFT -0.71%
Azure are the behemoths in the public cloud market; both organizations
sell (or rent) massive amounts of computing power to customers from their
Intel-dominated data centers.
Smith
has no problem stipulating that Intel owns “99 point whatever percent” of the
data center chip architecture, with a smattering of IBM-backed Power chips and
Oracle ORCL -1.42% SPARC chips here and there. Likewise, he
admits that Intel INTC 0.23% x86 chips work with everything, that Intel
fields a huge partner ecosystem of software, hardware and add-on providers, and
that it also owns the biggest-and-best fabrication facilities.
But,
he also insists that big changes over the past year are shifting the balance of
power. “There are a billion smartphones out there with ARM chips,” Smith noted.
As a result, there many manufacturers and plenty of ARM licensees working with
the technology. What that means is ARM now has an ecosystem all its own, which
is something Softbank and Packet hope to capitalize on.
Taking
on established cloud giants like Amazon Web Services is a long shot but there
are some critical nuances to consider.
First,
the market for rentable computer resources is growing fast enough now to float
many boats, including newcomers, provided they have funding and innovative
services that corporate developers and their IT strategy overlords want.
Second,
even cloud giants admit that new chip technologies will be critical as cloud
computing matures. Energy-efficient ARM chips that already power an estimated
95% of smartphones are bound to get a look, especially if their use can reduce
data center power requirements. Microsoft and Google also talk up x86
alternative chips for some uses. And Amazon last year bought Annapurna Labs, an
ARM chip licensee. Clearly, there is interest here.
Smith
contended that the widespread use of ARM chips in other scenarios is also
making it easier for cloud service providers (and others) to get early previews
of the technology and to develop offerings using it.
Cavium and Leading Partners Showcase ThunderX® ARM-based Server Platforms, QLogic® FastLinQ Ethernet Adapters and Fibre Channel HBAs for High Performance Computing at SC16
SALT LAKE CITY, Nov. 15, 2016 --
Cavium, Inc. (NASDAQ: CAVM), a leading provider of semiconductor
products that enable intelligent processing for enterprise, data center,
cloud, wired and wireless networking, today announced the showcasing of
ThunderX based workload optimized server platforms and the QLogic
FastLinQ Ethernet Adapters and Fibre Channel HBAs for High Performance
Computing, Data Analytics, Scale Out Storage and Hyperscale Data Centers
at SC16 in the Salt Palace Convention Center in Salt Lake City, Utah. The show Expo dates are from Monday, November 14th to Thursday, November 17th.
ThunderX is Cavium's 64-bit ARMv8server processor family
for next generation high performance computing and hyperscale
workloads. With up to 48 high-performance custom cores, single and dual
socket capability, high memory bandwidth and capacity, and integrated
hardware accelerators, ThunderX enables best-in-class ARMv8 performance
per dollar and performance per watt. The ThunderX family includes
multiple SKUs that enable servers optimized for compute, storage,
network and security workloads in the cloud, and is widely supported by
industry-leading OS, hypervisor, software tool and application vendors.
ThunderX is also optimized for networking specific workloads such as
Network Functions Virtualization (NFV).
From
the heart of the data center, to the edge of the enterprise, and in the
cloud, QLogic® Fibre Channel and Ethernet adapters deliver an
uncompromising suite of features, performance and reliability with a
comprehensive suite of offerings that span 10GbE to 100GbE, and 8GFC to
32GFC (Gen6). QLogic Fibre Channel adapters are the gold standard in
SAN connectivity, trusted with running mission critical applications
across the world, and the QLogic FastLinQ Ethernet adapters are the most
flexible data networking solutions in the industry supporting FCoE,
iSCSI and RDMA transports. Together, these products make Cavium the
industry leader in high performance network connectivity solutions.
Show Highlights and Demonstrations
Cavium
executives will be available to discuss the broad range of ThunderX
based production platforms, which are ideal for critical workloads such
as highly parallel HPC applications, scale out storage with CEPH, Apache
Hadoop for Big Data Analytics, distributed data bases such as MySQL
& Cassandra, and Web Serving with NGINX. In addition to the ThunderX
based ODM and OEM platforms, Cavium's QLogic® FastLinQ Ethernet
Adapters and Fibre Channel HBAs will be on display at Cavium's booth
#4057 including:
- QLogic FastLinQ 10/25/40/50/100 Gb Ethernet Adapters
- QLogic Enhanced Gen5 and Gen6 Fibre Channel Adapter
- ThunderX System Partners including: Aewyn, E4, Gigabyte and Lenovo
Cavium
representatives will also be presenting more details on ThunderX at a
number of partner sponsored events during the week. These events
include the ARM HPC User Group as well as presentations at the Red Hat
and SUSE booths during the week at the Convention Center.
To schedule a meeting at SC16, please send an email to sales@cavium.com and enter SC16 Meeting Request in the subject line.
About Cavium
Cavium, Inc. (NASDAQ: CAVM), offers a broad portfolio of integrated, software compatible processors ranging in performance from 1Gbps to 100Gbp that enable secure, intelligent functionality in Enterprise, Data Center, Broadband, Mobile and Service Provider Equipment, highly programmable switches which scale to 3.2Tbps and Ethernet and Fibre Channel adapters up to 100Gbps. Cavium processors are supported by ecosystem partners that provide operating systems, tools and application support, hardware reference designs and other products. Cavium is headquartered in San Jose, CA with design centers in California, Massachusetts, India, Israel, China and Taiwan.
Cavium, Inc. (NASDAQ: CAVM), offers a broad portfolio of integrated, software compatible processors ranging in performance from 1Gbps to 100Gbp that enable secure, intelligent functionality in Enterprise, Data Center, Broadband, Mobile and Service Provider Equipment, highly programmable switches which scale to 3.2Tbps and Ethernet and Fibre Channel adapters up to 100Gbps. Cavium processors are supported by ecosystem partners that provide operating systems, tools and application support, hardware reference designs and other products. Cavium is headquartered in San Jose, CA with design centers in California, Massachusetts, India, Israel, China and Taiwan.
Media Contact
Angel Atondo
Sr. Marketing Communications Manager
Telephone: +1 408-943-7417
Email: angel.atondo@cavium.com
Angel Atondo
Sr. Marketing Communications Manager
Telephone: +1 408-943-7417
Email: angel.atondo@cavium.com
At the World Robot Conference 2016, which ran from Friday to Tuesday in a southern suburb of Beijing, some companies complained that the event is unlikely to help them due to the overheated market. Manufacturers looking to automate have had a hard time finding workers to operate their robots, and the industry is still struggling with how to better integrate operation systems. The frenzy in China's robotics market is cooling, and people are raising more practical questions about how to best implement robotics in manufacturing.
Beijing-based Yaskawa Shougang Robot Co showcases its industrial robots at the World Robot Conference 2016 in Beijing. Photo: Chen Qingqing/GT
On
a chilly Friday afternoon, dozens of attendees at the World Robot Conference
2016 in suburban Beijing gathered around an industrial robotic arm
demonstrating its delicate grip and wide range of motion.
The
six-axis robotic arm can be used in a wide range of applications such as
assembly, dispensing, materials handling and packaging.
"I
am not surprised by the progress these exhibitors have made in automation. I
know many Chinese factories are equipped with industrial robots to increase
efficiency," an attendee surnamed Zhang told the Global Times on Friday at
the conference, which ended on Tuesday.
China
has been considered a growth market for industrial robots over the last few
years, Vitaly Nedelskiy, president of the Russian Association of Robotics, said
at the conference on Friday.
China's
supply of industrial robots grew by a robust 17 percent in 2015, Nedelskiy
noted. Companies installed 68,000 robots last year, though the ratio of robots
to workers remains far below the global average.
Globally,
the average ratio of robots to workers, known in the industry as robot density,
stood at 69 installed robots for every 10,000 employees in 2015, according to
the International Federation of Robotics (IFR).
By
comparison, China's average robot density is about 49 robots per 10,000
workers, Nedelskiy noted.
Under
its "Made in China 2025" or China's "Industry 4.0," the
Chinese government has set a target for China to have 150 robots per 10,000
workers by 2020.
To
achieve the goal, the country's industrial enterprises would have to add
600,000 to 650,000 industrial robots by the end of the decade, according to the
IFR.
Because
the government is encouraging Chinese manufacturers to install more automated
machinery and robots to boost efficiency, about 3,400 companies around the
country are now engaged in the robotics business, domestic industry news site
robot.ofweek.com reported in May.
However,
the development of China's robotics industry has been uneven and the market has
grown overheated, leaving major challenges that need to be addressed, industry
experts said during the conference.
Men
and machines
Despite
the rapid growth of China's robotics industry, which had about 20 percent of
the domestic market share in 2015, the country lacks workers trained to run the
machines, said Qu Daokui, president of Shenyang SIASUN Robot & Automation
Co. The lack of workers is one of the major issues many Chinese factories are
facing today.
With
the government so clearly behind the robotics industry, factories have jumped
to acquire automated machinery. The city of Dongguan, South China's Guangdong
Province, often referred to as "the world's factory," has adopted a
strategy called "Robotics-powered Smart Manufacturing" to improve the
productivity of local manufacturers.
There
are nearly 200 robot manufacturers in Dongguan, according to a document the
local government sent to the Global Times in February. So far, 400 factories
have been equipped with a total of 10,000 robots.
Although
they have the robots, they still need people to operate them, said Qu, whose
company acquired a German vocational training institution in February.
"More
and more factories are asking us to teach them how to use [industrial robots],
instead of just installing them, which illustrates how important it is to
educate more skillful workers," Qu told the Global Times.
The
lack of trained workers has weighed on some small and medium-sized enterprises
(SMEs) in the Pearl River Delta, said an employee in charge of automation at an
original equipment manufacturer in Dongguan, who spoke on the condition of
anonymity. Dongguan is an industrial powerhouse in the Pearl River Delta
region.
The
situation also jeopardizes the government's goal of automating more of the
city's manufacturing industry.
"It's
hard to find sufficient skillful workers who can handle those machines, and
some factories only use automated machines when local officials visit their
production lines, and they go back to labor-intensive production after [the
officials] leave," the employee told the Global Times on Sunday.
The
factories benefit from the government subsidies they receive for rebranding
themselves as an "automated business," but few local SMEs actually
benefit from installing industrial robots, the employee said.
As
it turns out, operating a robot is a multidisciplinary task involving the
integration of software, hardware and core technologies, experts said.
A
lot of people just think "I'll buy a robot and place it and connect
it", but they end up with a lot of problems, said Oussama Khatib, director
of robotics laboratory at Stanford University.
Technology
and the future
For
those who focus on research and development (R&D) in the robotics sector,
more effort needs to be made to make the machine smarter by introducing more
advanced technologies, but China has a long way to go, industry representatives
said.
The
rise of China's robotics industry has encouraged a growing number of companies
to enter the field, but many of them don't bother with developing their own
core technology and stick to manufacturing low-end products, said Gan Zhongxue,
chief technology officer of the ENN Group.
"Some
elements like the RV reducer and controller are still produced by foreign
companies," he told the Global Times on Friday. An RV reducer, one of
reduction gears, is used for transmission and the controller is used for
controlling the machine.
Purchasing
those components from overseas raises the manufacturing costs for Chinese
robotics companies.
As
far as technological trends are concerned, companies will be concentrating on
the collaboration between humans and machines, simplified applications and
light-weight robots, the IFR said in its World Robotics Report 2016.
And
the demand for industrial robots will likewise be driven by a whole assortment
of factors, such as the handling of new materials, energy efficiency, and
better developed automation concepts, the report said.
For
now, a large part of industrial robots are operating under digital control
systems, but a more harmonized human-robot interaction requires greater
flexibility and autonomous operation in unstructured environments, which is
unlikely to be achieved for the moment, said Zuo Shiquan, head of the equipment
industry institute at the CCID Institute affiliated with the Ministry of
Industry and Information Technology.
"Although
the application of robots in China has expanded in recent years, the next step
ought to be to improve R&D, which will help keep us from falling behind our
foreign competitors," he told the Global Times.
By Chen Qingqing Source:Global Times Published: 2016/10/24 19:38:39
Google’s Making Its Own Chips Now. Time for Intel to Freak Out
The
Internet’s most powerful company sent a few shock waves through the tech world
yesterday when it revealed that a new custom-designed chip helps run what is
surely the future of its vast online empire: artificial intelligence.
In
building its own chip, Google has taken yet another step along a path that has
already remade the tech industry in enormous ways. Over the past decade, the
company has designed all sorts of new hardware for the massive data centers
that underpin its myriad online services, including computer servers,
networking gear, and more. As it created services of unprecedented scope and
size, it needed a more efficient breed of hardware to run these services. Over
the years, so many other Internet giants have followed suit, forcing a seismic
shift in the worldwide hardware market.
With
its new chip, Google’s aim is the same: unprecedented efficiency. To take AI to
new heights, it needs a chip that can do more in less time while consuming less
power. But the effect of this chip extends well beyond the Google empire. It
threatens the future of commercial chip makers like Intel and
nVidia—particularly when you consider Google’s vision for the future. According
to Urs Hölzle, the man most responsible for the global data center network that
underpins the Google empire, this new custom chip is just the first of many.
No,
Google will not sell its chips to other companies. It won’t directly compete
with Intel or nVidia. But with its massive data centers, Google is by far the
largest potential customer for both of those companies. At the same time, as
more and more businesses adopt the cloud computing services offered by Google,
they’ll be buying fewer and fewer servers (and thus chips) of their own, eating
even further into the chip market.
Indeed,
Google revealed its new chip as a way of promoting the cloud services that let
businesses and coders tap into its AI engines and build them into their own
applications. As Google tries to sell other companies on the power of its AI,
it’s claiming—in rather loud ways—that it boasts the best hardware for running
this AI, hardware that no other company has.
Google’s
Need for Speed
Google’s
new chip is called the Tensor Processing Unit, or TPU. That’s because it helps
run TensorFlow, the software engine that drives the Google’s deep neural
networks, networks of hardware and software that can learn particular tasks by
analyzing vast amounts of data. Other tech giants typically run their deep
neural nets with graphics processing units, or GPUs—chips that were originally
designed to render images for games and other graphics-heavy applications.
These are well-suited to running the types of calculations that drive deep
neural networks. But Google says it has built a chip that’s even more
efficient.
According
to Google, it tailored the TPU specifically to machine learning so that it
needs fewer transistors to run each operation. That means it can squeeze more
operations into the chip with each passing second.
For
now, Google is using both TPUs and GPUs to run its neural nets. Hölzle declined
to go into specifics on how exactly Google was using its TPUs, except to say
that they handle “part of the computation” needed to drive voice recognition on
Android phones. But he said that Google would be releasing a paper describing
the benefits of its chip and that Google will continue to design new chips that
handle machine learning in other ways. Eventually, it seems, this will push
GPUs out of the equation. “They’re already going away a little,” Hölzle says.
“The GPU is too general for machine learning. It wasn’t actually built for
that.”
That’s
not something nVidia wants to hear. As the world’s primary seller of GPUs,
nVidia is now pushing to expand its own business into the AI realm. As Hölzle
points out, the latest nVidia GPU offers a mode specifically for machine
learning. But clearly, Google wants the change to happen faster. Much faster.
The
Smartest Chip
In
the meantime, other companies, most notably Microsoft, are exploring another
breed of chip. The field-programmable gate array, or FPGA, is a chip you can
re-program to perform specific tasks. Microsoft has tested FPGAs with machine
learning, and Intel, seeing where this market was going, recently acquired a
company that sells FPGAs.
Some
analysts think that’s the smarter way to go. An FPGA provides far more
flexibility, says Patrick Moorhead, the president and principal analyst at Moor
Insights and Strategy, a firm that closely follows the chip business. Moorhead
wonders if the new Google TPU is “overkill,” pointing out that such a chip
takes at least six months to build—a long time in the incredibly competitive
marketplace in which the biggest Internet companies compete.
But
Google doesn’t want that flexibility. More than anything, it wants speed. Asked
why Google built its chip from scratch rather than using an FPGA, Hölzle said:
“It’s just much faster.”
Core
Business
Hölzle
also points out that Google’s chip doesn’t replace CPUs, the central processing
units at the heart of every computer server. The search giant still needs these
chips to run the tens of thousands of machines in its data centers, and CPUs
are Intel’s main business. Still, if Google is willing to build its own chips
just for AI, you have to wonder if it would go so far as to design its own CPUs
as well.
Hölzle
plays down the possibility. “You want to solve problems that are not solved,”
he says. In other words, CPUs are a mature technology that pretty much works as
it should. But he also said that Google wants healthy competition in the chip
market. In other words, it wants to buy from many sellers—not just, say, Intel.
After all, more competition means lower prices for Google. As Hölzle explains,
expanding its options is why Google is working with the OpenPower Foundation,
which seeks to offer chip designs that anyone can use and modify.
That’s
a powerful idea, and a potentially powerful threat to the world’s biggest chip
makers. According to Shane Rau, an analyst with research firm IDC, Google buys
about 5 percent of all server CPUs sold on Earth. Over a recent year-long
period, he says, Google bought about 1.2 million chips. And most of those
likely came from Intel. (In 2012, Intel exec Diane Bryant told WIRED that
Google bought more server chips from Intel than all but five other
companies—and those were all companies that sell servers.)
Whatever
its plans for the CPU, Google will continue to explore chips specifically
suited to machine learning. It will be several years before we really know what
works and what doesn’t. After all, neural networks are constantly evolving as
well. “We’re learning all the time,” he says. “It’s not clear to me what the
final answer is.” And as it learns, you can bet that the world’s chip makers
will be watching.
