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Wednesday, December 04, 2019

CodeGuru gives automated code reviews and application performance recommendations

By Nick Flaherty

Amazon has launched a cloud-based machine learning service for development teams who want to automate code reviews, identify the most expensive lines of code in their applications, and receive intelligent recommendations on how to fix or improve their code.

Even for the most seasoned engineers, it can be difficult to detect some types of code issues even through peer code reviews and unit testing. It can also be challenging to identify the most resource intensive code methods without needing performance engineering expertise. CodeGuru, based on the AWS cloud service, helps developers catch code issues faster and earlier, and improve application performance.

CodeGuru Reviewer detects and flags wide-ranging issues in source code such as thread safety issues, use of un-sanitized inputs, inappropriate handling of sensitive data, and resource leaks. It also detects deviation from best practices for using AWS APIs and SDKs, flagging common issues that can lead to production issues, such as detection of missing pagination or error handling with batch operations. 

It is based on machine learning models trained on Amazon’s internal code bases of hundreds of thousands of internal projects, as well as over 10,000 open source projects in GitHub. Tens of thousands of Amazon developers have contributed to CodeGuru’s training based on decades of experience in code review and application profiling. 

For example, CodeGuru Reviewer is trained using rule mining and supervised machine learning models that use a combination of logistic regression and neural networks. During training to detect deviation from best practices, it mines Amazon code bases for pull requests that include AWS API calls. It looks at code changes and cross-references them against documentation data, which it also mines in parallel. This creates new models for best practices that Reviewer uses when it reviews the code to provide recommendations. CodeGuru Profiler is also trained by Amazon performance engineers and used to profile tens of thousands of services used internally at Amazon. 

The Profiler searches for application performance optimizations, identifying the most “expensive” lines of code and recommending ways to fix them to reduce CPU utilization, cut compute costs, and improve application performance. This provides specific recommendations so developers can take action immediately on issues such as excessive recreation of expensive objects, expensive deserialization, usage of inefficient libraries, and excessive logging. It also runs continuously in production, consuming minimal CPU capacity so it does not significantly impact application performance. 

To use the service, developers can associate existing code repositories on GitHub or AWS CodeCommit with CodeGuru. Profiling an application starts by installing a small agent using code that CodeGuru provides and configuring it in the CodeGuru console.

CodeGuru is available in preview in the AWS regions of US East (N. Virginia), US East (Ohio), US West (Oregon), EU (Ireland), and Asia Pacific (Sydney).

Amazon CodeGuru

Kontron Box PC industrial controllers use Intel Core and Xeon E processors

By Nick Flaherty

Kontron has launched its third generation of industrial computers in Box PC format using Intel Core and Xeon E processors 
The KBox C-103-CFL series is based on the latest of the ninth generation with up to six processor cores and are specifically designed for use in control cabinets in automation environments. In addition to the control and visualization of machines or inspection and AI-based vision applications, Soft-PLC applications can also be implemented using the optional NVRAM and the integration of fieldbus extensions. The KBox C-103-CFL is currently available with two PCI Express slots; further variants with up to four slots will follow during the first quarter of 2020. 

The Bix PCs use the ninth generation Core i3, i7 or Xeon E processors; the Intel Core i5 is based on the 8th generation. The maintenance-free system enables fanless operation up to 75 degrees Celsius while a Goldcap option and redundant power supplies as well as the recovery functionality guarantee maximum system availability and a long life time.

In addition to up to three display ports and up to four GB Ethernet interfaces, the family features up to four PCI Express, one mPCIe and three M.2 expansion slots. Up to two COM ports incl. RS485 option, three USB 3.0 and three USB 2.0 ports,as well as up to four SATA slots ensure maximum flexibility and expandability. For secure communication and connection to the cloud, the industrial computers support TPM V2.0 encryption and the Kontron APPROTECT security solution based on Wibu-Systems CodeMeter. Kontron APPROTECT Licensing also enables new business models such as 'pay-per-use' or time-based trial versions.

Tuesday, December 03, 2019

AMD gets back into the embedded market with focus on mini PCs

By Nick Flaherty

AMD has made its return to the embedded market with Ryzen Embedded V1000 and R1000 processors.

These are being used by ASRock Industrial, EEPD, OnLogic and Simply NUC for Mini PC platforms for the industrial, media, communications and enterprise markets with a planned 10-year processor availability.

“The demand for high performance computing isn’t limited to servers or desktop PCs. Embedded customers want access to small form factor PCs that can support open software standards, demanding workloads at the edge, and even display 4K content, all with embedded processors that have a planned availability of 10 years,” said Rajneesh Gaur, corporate vice president and general manager of  Embedded Solutions, AMD. “This is why many of our technology partners have chosen AMD Ryzen Embedded processors to power their Mini PCs. We are excited to work together and provide the industry with a new open ecosystem for small form factor computing.”

The value this time, says AMD, is the Mini PCs have access to an existing embedded processor ecosystem that supports open software standards, while providing OEMs the capability to create unique, customisable platforms.

The AMD Ryzen Embedded processors combine the Zen CPU and Vega GPU architectures in an SoC with a power envelope from 6W to 54W in pin compatible packages that powers high resolution, 4K multi-display configurability and high-performance 3D graphics.

The key is that the Mini PCs support a growing list of software partners with pre-validated packages based on open source software. These partners include Radeon Open Compute (ROCm), OpenCL™, and more. As well, these Mini PCs can run software for machine vision, object detection, edge inference, and analytics from AMD software ecosystem partners, creating a platform that’s well suited for applications that require fast deployment.

ASRock Industrial with its 4X4 BOX – R1000V and 4X4 BOX – V1000M systems aim to deliver cost-effective, high-performance and versatile embedded Mini PCs for home entertainment, business and industrial applications.
EEPD's SBC PROFIVE NUCV and SBC PROFIVE NUCR embedded Mini PC product family is focussed on minimal space
OnLogic's ML100G-40 and MC510-40 are the first two systems in a line of AMD powered small form-factor computers that leverage the reliability and lifecycle benefits of OnLogic's expertise in building industrial and rugged devices.
Simply NUC with the Sequoia V8 and Sequoia V6, which are rugged, long-lasting units to power digital signage displays, electronic kiosks, data arrays, and other free-standing utilities

"Simply NUC has excelled in making small form factor PCs for a while, but when we took a look at our product roadmap, we noticed a gap in providing our customers with high-performance, long life platforms," said Aaron Rowsell, CEO at Simply NUC. "With the new Simply NUC Sequoia platform, we get to take the high-performance capabilities and planned longevity of the AMD Ryzen Embedded processors and combine that with the Simply NUC experience and create a minicomputer that’s small in size but not on toughness or reliability.”

Monday, December 02, 2019

Adlink teams for machine vision AI at the edge

By Nick Flaherty

Camera maker ADLINK Technology has teamed up with Intel and Amazon Web Services (AWS) to simplify artificial intelligence (AI) at the edge for machine vision. 

The integrated solution offers an Amazon Sagemaker-built machine learning model optimized by and deployed with the Intel Distribution of OpenVINO toolkit, the ADLINK Edge software suite, and certification on AWS Greengrass.

The approach provides the full cycle of machine learning model building—from design to deployment to improvement—by automating edge computing processes so that customers can focus on developing applications without needing advanced knowledge of data science and machine learning models: 

  • The Intel Distribution of OpenVINO toolkit optimizes deep learning workloads across Intel architecture, including accelerators, and streamline deployments from the edge to the cloud.
  • Amazon Sagemaker is  a fully-managed service that covers the entire machine learning workflow.
  • AWS Greengrass extends AWS to edge devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage.
  • The ADLINK Data River offers translation between devices and applications to enable a vendor-neutral ecosystem to work seamlessly together.
“We’ve worked on multiple industrial use cases that benefit from AI at the edge, including a smart pallet solution that makes packages and pallets themselves intelligent so they can detect where they're supposed to be, when they're supposed to be there, in real-time,” said Toby McClean, VP, IoT Innovation & Technology, at ADLINK. “This enables warehouse customers to yield improved logistics and productivity, while also decreasing incorrectly shipped packages and theft. And this use case can be replicated across verticals to improve operational efficiency and productivity.”

Additional use cases include object detection modeling for object picking functions or worker safety, such as identifying product defects on conveyor systems or worker impediments in manufacturing environments, and equipment failure predictions to reduce machine downtime and increase productivity.

The software can be fully optimized on certified ADLINK devices, including the NEON industrial smart camera, EOS vision system, and deep learning accelerator card and GigE frame grabber with Intel's Movidius Myriad X VPU.

Hybrid wafers with GaN on Si ... Spin computing slashes power ... In-panel batteries to boost storage

Power news from eeNews Europe Power by Nick Flaherty

. Spin computing slashes power consumption

. Nexans signs wind turbine power cable deal with Siemens Gamesa

. Swedish 50kW fast charger roll out uses ABB tech

. Silicon-carbon anode startup raises $18m

. Graphene battery electrode for in-panel storage

. Hybrid GaN-on-SiC wafers boost for power devices

. 300Farad UL-certified ultracapacitor for robotics and smart factories

. 1U programmable power supply reaches 3.4kW

. 600A, 60mm bipolar thyristor module targets drives and UPS