Intel Corp INTC is set to report first-quarter 2017 results on Apr 27, after the closing bell. Notably, the company has positive record of earnings surprises in the trailing four quarters, with an average surprise of 9.11%.

Last quarter, the company posted a positive earnings surprise of 5.33%. Non-GAAP earnings of 79 cents per share increased almost 4% from the year-ago quarter but declined 1.3% sequentially.

Strong year-over-year earnings growth was driven by 9.8% increase in revenues, which totaled $16.37 billion and comfortably surpassed the Zacks Consensus Estimate of nearly $15.80 billion. Revenues increased 3.8% sequentially.

Skyworks Solutions, Inc. Price and EPS Surprise

Skyworks Solutions, Inc. Price and EPS Surprise | Skyworks Solutions, Inc. Quote

Intel guided first-quarter 2017 revenues of around $14.8 billion (+/-$500 million), almost flat sequentially. The non-GAAP gross margin is expected to be around 63% (+/-1%). R&D and MG&A expenses are anticipated to come in at around $5.3 billion.

Operating income is projected to be approximately $4.1 billion, while earnings are anticipated to be 65 cents (+/- 5 cents) per share.

The lacklustre guidance along with declining growth in core PC and data center markets has hurt share price movement on a year-to-date basis. Intel shares have inched up 0.2% as compared with the Zacks Semiconductor General industrys gain of 2.1%.

Lets see how things are shaping up for this announcement.

Factors at Play

We note that Intels growing focus into areas with better growth prospects, such as the artificial intelligence (AI), autonomous car and Internet of Things (IoT) businesses are key catalysts.

In this regard, the acquisition of Mobileye is a significant development that will boost its presence in the autonomous vehicle market. Further, the recently completed divestiture of the security business will help the company to focus on these fast growing businesses.

However, increasing competition in the data center market is a headwind. Reportedly, Microsoft is collaborating with ARM chip-makers Qualcomm QCOM and Cavium to design ARM-based servers, which will run a major part of its cloud services going ahead. (Read More: Microsoft Says Yes to ARM-Based Chips for its Cloud Servers)

Moreover, per IDC data worldwide server shipments decreased 3.5% year over year to 2.55 million units in fourth-quarter of 2016. The research firm cited slowdown in hyperscale datacenter growth and continued drag from declining high-end server sales as the primary reason behind this decline.

The data center business now comprises a major part of Intels overall business (29% of 2016 revenues). Hence, a decline in the server shipment amid intensifying competition is a major concern for the company.

Moreover, sluggish PC market growth will also continue to hurt Client Computing Group (55.8% of revenues) growth. Despite strong PC shipments in the first quarter as per data available from both Gartner and IDC we believe they are not sufficient enough to drive significant growth for the segment in the near term. (Read More: Strong PC Shipments Witnessed in Q1: Gartner, IDC)

Earnings Whispers

Our proven model does not conclusively show that Intel will beat earnings this quarter. This is because a stock needs to have both a positive Earnings ESP and a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 (Hold) for this to happen. That is not the case here as you will see below.

Zacks ESP: Both the Most Accurate estimate and the Zacks Consensus Estimate are pegged at 65 cents. Hence, the difference is 0.00%. You can uncover the best stocks to buy or sell before theyre reported with our Earnings ESP Filter.

Zacks Rank: Intel carries a Zacks Rank #4 (Sell). We caution against stocks with a Zacks Rank #4 or 5 (Sell-rated stocks) going into the earnings announcement, especially when the company is seeing negative estimate revisions.

Stocks to Consider

You could consider the following stocks with a positive Earnings ESP and a favorable Zacks Rank:

Teradyne TER, with an Earnings ESP of +2.63% and a Zacks Rank #1. You can see the complete list of todays Zacks #1 Rank stocks here.

Seagate Technology STX, with an Earnings ESP of +3.77% and a Zacks Rank #2.

Read More

Follow this link:
Intel (INTC) to Report Q1 Earnings: What's in the Cards? - Yahoo Finance

The way that virtualisation has been talked about over the last decade you would be tempted to think every server and storage system has had the virtualisation treatment, but many organisation still haven't completely climbed on board the virtualisation ship headed for cloud nirvana. That said, there is still time and the benefits still stand.

According to Kong Yang, head geek at SolarWinds, virtualisation can bring many benefits to a business, from cost savings and flexibility to making IT workflows and processes more efficient and effective. "However, one of the key benefits is the ability to abstract infrastructure resources, which allows for the re-distribution of resources to applications at a radically faster rate," he says.

He adds the need to embrace virtualisation comes hand-in-hand with growing hybrid IT environments. The recent SolarWinds IT Trends Report 2017 reflects this, as it shows 52% of companies have server virtualisation included within their hybrid IT strategy.

Yang says hybrid IT is very much a reality for UK businesses, as many host some of their infrastructure in the cloud while also maintaining some on-premises. "In fact, our research shows that in the past 12 months, UK organisations have migrated applications (69%), storage (54%), and databases (37%) to the cloud -- this is more than any other area of IT," he says.

Consolidating servers and storage

So, what's the best way to go about consolidating servers and storage with virtualisation? It is critical to first understand the objectives of the virtualisation project and the outcomes that are desired. Often virtualisation forms part of a larger project, such as an application re-platform or datacentre consolidation or migration and it's important to understand how the larger picture affects the specific project.

"Once the objectives are clear, organisations should consider the individual workloads and operational areas to be implemented and how the implementation programme is to be conducted," says Pete Hulme, data centre technical lead at Dimension Data.

"For example, is it acceptable (or desirable) for test and development to share a platform with production? And is it important to be able to produce 'clones' of production for test purposes?"

He adds that companies should consider how business continuity and disaster recovery will be conducted and how the data management tools interact with the virtualisation platform. Adding, they should consider how security and segmentation is to be managed and who is to hold authority and control.

"Once these decisions are made it should then be possible to select a virtualisation platform for each component and to understand how these will interact and interoperate. It is essential to consider the management platform and interfaces that will be required to deploy and operate the platform and how the processes will interact with both new and existing processes," Hulme says.

Best practices

When virtualising infrastructure there are several best practices to be aware of. All x86 servers are now candidates for virtualisation. But according to Richard Stinton, enterprise solutions architect at iland, the main blockers to virtualisation are normally the risk associated with the migration process, especially downtime, and licensing policies of the software being run, the best example being Oracle.

"For this reason, the main servers still running on physical tend to be large transactional databases, such as SQL Server clusters, and Oracle," he says.

David Cottingham, director of XenServer product management and partner engineering at Citrix, says organisations should understand the characteristics of the workloads it is trying to virtualise, in terms of their CPU, memory, and I/O needs.

"A classic problem in virtualisation is for an overly-optimistic administrator to attempt to pack too many virtual machines onto a server and the end users experiencing poor performance when load is high," he says.

Technologies such as dynamic memory control and storage caching can help pack more VMs per server, workload balancing technologies can also support, "especially where VMs' performance is recorded over time, and then recommendations can be made on how to change the distribution of VMs across physical servers," Cottingham adds.

For storage, different issues come into play. Tom O'Neill, CTO international at all-flash storage provider Kaminario, believes the most important aspect of virtualising storage is to ensure the performance and capacity aspect are sized correctly.

"Storage is often the slowest part of any IT project and virtualised workloads often drive storage solutions harder," he says.

This is due to the I/O blender effect of multiple layers of virtualisation. Friendly sequential I/O can become increasingly random as extra layers of virtualisation are introduced. The impact of random vs sequential is much reduced with modern storage media like flash, but it's still considerable because of the caching and CPU deployed within the storage device (SSD).

Virtualising to move to the cloud

Virtualisation can also be considered a stepping stone to the cloud. However, if organisations opt for a private cloud, they should have a few resources in place - VM templates, resource pools, a user interface for self-service and a request process.

"VM templates let individuals requesting a new VM provision [it] themselves automatically, while resource pools designate a maximum quantity of resources that an end user can consume," says Arun Balachandran, product manager, at ManageEngine. "Organisations should also select the right tool as a user interface for self-service and have a request process in place."

He adds that in moving to private cloud, organisations must confirm that it remains cost-effective by means of constant performance monitoring and capacity planning.

"Without right-sizing VMs and failing to track and anticipate resource needs, businesses could face problems such as VM sprawl and resource overconsumption. Businesses should plan for the long term to ensure they have enough resources on hand to meet future business demands. To keep costs low, they can use low cost hypervisors or hypervisors from multiple vendors," he concludes.

Excerpt from:
Getting to grips with server and storage virtualisation - Cloud Pro

IBM has announced an expansion to the developer console for the companys cloud platform, Bluemix.

The expanded developer console will include templates of applications that are ready to code to user specification. The templates include database integration, as well as cognitive and security services.

This is expected to significantly reduce the amount of time it takes for developers to set up microservices and roll out applications. Using the templates as building blocks for applications, rather than starting from scratch, developers can easily and quickly create cloud apps across mobile, web, and backend systems.

Bluemix developers can nowaccess the dashboard to create a customized template that includes the type of building block they would like to create, followed by the type of services they want to incorporate into the new app. Once a language is determined, the console generates a project pattern that can then be downloaded and edited to user specifications. Upon completion, the application may be deployed locally or directly to Bluemix.

The new expansion includes the Mobile App template, which allows developers to create applications that integrate with mobile services such as Push and Mobile Analytics. It also includes Backend for Frontend, which integrates backend patterns such as data, security, and cognitive intelligence into new applications. A template for WebApp is available, to assist in the development of a client-side web app using tools like Gulp, Sass, and React.

The developer console expansion also builds on last weeks announcement of new techniques for writing Bluemix-compatible microservices in a variety of languages, creating the flexibility for enterprises to assign several different developers to work on an app in different languages.

Now, with the expanded developer console, users can access microservice templates to get starter code for a single function that can be reused across multiple clients, with built-in Dockerfile to run the microservice in Docker container environments.

The expansion also includes integration with data services IBM Cloud Object Storage and Cloudant, and security services using AppID.

Earlier this month, IBM announced that Bluemixwould become the first major global cloud provider to make the NVIDIA Tesla P100 GPU accelerator available on the IBM Cloud platform. Clients are now able to equip IBM Bluemix bare metal cloud servers with NVIDIA accelerators, helping enterprises to run compute-heavy workloads including AI and analytics more quickly and efficiently.

Read the rest here:
IBM expands Bluemix cloud developer console - The Stack

An explosion in cloud services is making chip design for the server market more challenging, more diverse, and much more competitive.

Unlike datacenter number crunching of the past, the cloud addresses a broad range of applications and data types. So while a server chip architecture may work well for one application, it may not be the optimal choice for another. And the more those tasks become segmented within a cloud operation, the greater that distinction becomes.

This has set off a scramble among chipmakers to position themselves to handle more applications using more configurations. Intel still rules the datacentera banner it wrestled awayfrom IBM with the introduction of commodity servers back in the 1990sbut increasingly the x86 architecture is being viewed as just one more option outside of its core number-crunching base. Cloud providers such as Amazon and Google already have started developing their own chip architectures. And ARM has been pushing for a slice of the server market based upon power efficient architectures.

ARMs push, in particular, is noteworthy because it is starting to gain traction in a number of vendors server plans. Microsoft said last month it would use ARM server chips in its Azure cloud business to cut costs. This seemed like dream just a couple years ago, but a lot of people are putting money into it big time right now, said Kam Kittrell, product management group director in the Digital & Signoff Group at Cadence. As time goes on, what well see is that is instead of just having a general-purpose server farm that runs at different frequencies but basically has a different chip in it (depending if its high performance or not), youre going to see a lot of different types of compute farms for the cloud.

Fig. 1: ARM-based server rack. Source: ARM

Whether ARM-based servers will succeed just because they use less power than an x86 chip for specific workloads isnt entirely clear. Unlike consumer devices, which typically run in cycles of a couple years, battles among server vendors tend to move in slow motionsometimes over a decade or more. But what is certain is that inside large datacenters, power expended for a given workload is a competitive metric. Powering and cooling thousands of server racks is expensive, and the ability to dial power up and down quickly and dynamically can save millions of dollars per year. Already, Google and Nvidia have publicly stated that a different architecture is required for machine learning and neural networking.

In looking at the power performance tradeoffs, and how to target the designs properly, there are two distinct things that cloud has accelerated in both the multicore and networking space. What is common between these chips is that they are pushing whatever the bleeding edge is of technology, such as 7nm, Kittrell said. Youve got to meet the performance, theres no question. But youve also got to take into account the dynamic power in the design. At 65nm we got used to power being dictated by leakage all the way through 28nm. At 28nm, which was the end of planar transistor, dynamic power became more dominant. So now youre having to study the workloads on these chips in order to understand the power. Even today, datacenters use 2% of the power in the United States, so they are a humongous consumer. And when it comes to power, its not just how much power the chip uses, its the HVAC in order to keep the datacenter cool. In essence, youve got to keep the dynamic power under target workloads under control, and the area has to be absolutely as small as possible. Once you start replicating these things, it can make a tremendous difference in the cost of the chip overall. The more switching nodes you put in there, the more power it consumes overall.

Slicing up the datacenter Changes have been quietly infiltrating datacenters for some time. While there are still racks of servers humming along in most major data centers, a closer look reveals that not all of them are the same. There are rack servers, networking servers, and storage servers, and even within those categories the choices are becoming more granular.

While there is still a need for enterprise data centers to have a general server/traditional server primarily based on Intel Xeon-core-based processors with a separate NIC card connecting to external networking where the switching and routing occur, we see in these large-scale cloud datacenters that they have a number of specific applications that they feel can be optimized for those applications within the cloud, within that data center, said Ron DiGiuseppe, senior strategic marketing manager in the Solutions Group at Synopsys.

As an example, DiGiuseppe pointed to Microsofts Project Olympus initiative under its Azure business, which defines a server that is targeting different applications such as web services. Microsoft is large scale they are estimating that 50% of their data center capacity is allocated to web server applications. And obviously, every cloud data center would be different. But they wanted to have servers that can be optimized for the web applications. They announced last month that they have five different configurations of servers targeting segment-optimized applications.

Another example would be database services, he said. This is very fast, and therefore low latency search and indexing for databases, such as for financial applications. With that in mind, the system architectures are being optimized for those applications, and the semiconductor suppliers are architecting their chips to have acceleration capabilities tied to the end applications. Therefore, you could optimize semiconductor adding features to support those different segmented applications.

That could include a 64-bit ARM processor-based server chip or an Intel Xeon-based server chip in a database services application, where the database access is accelerated by adding very close non-volatile storage using SSDs or NAND Flash SSDs through PCI Express, which connects directly to the processor using NVMB protocol. The goal is to minimize latency and to be able to store and access commands.

Seeing through the fog While equipping the datacenters is one trajectory, a second one is reducing the amount of data that floods into a datacenter. There is increasing interest to be able to use the network fabric to do at least some of the signal processing, data processing, and DSP processing to extract patterns and information from the data. So rather than pushing all of this data up through the pipe into the cloud, the better option is to refine that data so only a portion needs to be processed in the cloud servers.

This requires looking at the compute equation from a local perspective, and it opens up even more opportunities for chipmakers. Warren Kurisu, director of product management in the embedded division at Mentor, a Siemens Business, said current engagements are focused on working with companies that build solutions for local processing, local data intelligence, and local analytics so that the cloud datacenters are not flooded with reams of data that clog up the pipes.

One of the key areas of focus here involves intelligent gateways for everything from car manufacturing to breakfast cereal and pool chemicals. It requires multicore processors in the gateway that can enable a lot of the fog processing, a lot of data processing in the gateway, he said. And that adds yet another element, which is security.

Security is the number one question, so we have made a very huge focus on being able to create a gateway that leverages hardware security built-in to the chip and the board and establish a complete software chain of trust so that anything that gets run and loaded onto that gateway any piece of software is authenticated and validated through cryptologythrough certificates and other things, Kurisu said. But you need some processing power to do just that sort of stuff. There needs to be some sort of hardware security available. One of our key demonstration platforms is on the NXP I.MX6 processor, which has a high-assurance boot feature in it. The high-insurance boot basically has a key burned into the silicon, and we can leverage that key to be able to establish that chain of trust. If there isnt that hardware mechanism enabled in the system, then we can leverage things like secure elements that might be on the board that would all do the same thing. There would be some sort of crypto element there or a key used to establish the whole chain of trust. A change in thinking The key to success comes down to thinking about these chip designs very holistically, Kurisu added, because when it comes to cloud in the datacenter, and if you think about Microsoft Azure or Amazon Web services or any of the others, the types of capabilities that are available from the cloud datacenter down to the actual embedded device, these things need to work in tandem. If you have a robot controller, and you need to do a firmware updateand you want to initiate that from the cloudhow that gets enabled on the end device is tied very explicitly into how the operation is invoked from the cloud side. What is your cloud solution? Thats going to drive what the embedded solution is. Youve got to think of it as a system, and in that way the stuff that happens in the datacenter is very closely related to the things that might seem very disconnected on the edge. But how the IoT strategy is implemented is somewhat tied together so it all has to be considered together.

It also could have an impact on chip designs within this market, and open doors for some new players that have never even considered tapping into this market in the past.

View original post here:
Cloud Computing Chips Changing - SemiEngineering