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Google Cloud Next Gen Xeon CPU, ZYNC Render, New API Editions and Pricing

Google Cloud Platform (GCP) recently formed a strategic alliance with Intel, that adds support Compute Engine of Intel’s next-generation Xeon Processor (codenamed Skylake) in early 2017.

At launch, the latest Custom Cloud solution based processor’s AVX-512 extensions will be available to Compute Engine’s standard, highmem, highcpu and custom machine types, to help optimize enterprise-class and HPC workloads, google said.

Google also noted that they would introduce additional Skylake extensions over time, as well as bigger and better VM instance types with more vCPUs and RAM for compute- and memory-intensive workloads.

Google continues its push of Cloud platform into media and entertainment since completing the acquisition of online video platform Anvato and a collaboration with Autodesk at NAB. And, now it expands ZYNC Render to support two new host platforms: SideFX Houdini and Maxon Cinema 4D.

This integration offer cost and prodcutivity benefits and brings in massive scalability and compute access to animation industry. Animators by leveraging power of GCP will be able to bring their projects to life.

Houdini, a leading package for complex 3D effects, now let users utilize up to 32,000 cores on GCP for their rendering projects. Instead, of purchasing, artists can render on-demand, paying on a per-minute basis with the full economic benefits of GCP.

The Maxon Cinema 4D integration, a popular package for creating motion graphics, enable its product first time through a cloud rendering service.

JFrog, which recently refactored its Artifactory SaaS offering onto GCP using Google Cloud Storage as its massively scalable object store, thus makes it possible for customers to co-locate their development and production environments.

The team also provisioning a scripted service to onboard new customers, which triggers to automatically set up and configure all layers in the service architecture as soon as a user register for a free trial, helping get up and running virtually instantly.

The new architecture is based on GCP services, mainly Google Compute Engine and Cloud Storage with four layers:

  • “Network Load Balancers, balance requests coming from the outside world into the front-end web Nginx stacks
  • Web servers based on stacked Nginx servers are responsible for internal application load balancing and proxying requests
  • Artifactory application servers
  • Data and Metadata Management using Google Cloud SQL and Cloud Storage. Cloud SQL manages the Artifactory internal database fundamental to the product’s checksum-based storage, and Cloud Storage is the application’s massively scalable object store, where all the binary artifacts are actually hosted,” JFrog team writes.
JFrog Artifactory SaaS deployment architecture on GCP

JFrog Artifactory SaaS deployment architecture on GCP

Google at the recently concluded Microsoft Connect() conference in NYC, join the Microsoft’s Technical Steering Group of the .NET Foundation.

“.NET is a key component in the modern enterprise, and the Google Cloud Platform (GCP) team has worked hard to ensure that .NET has first-class support on Google’s infrastructure, including excellent infrastructure for Windows,” google stated.

For years, “Google has offered .NET libraries for more than 200 of its cloud services.” More recently, Google also launched native GCP support for Visual Studio and PowerShell.

Early in 2017, Google said, “GCP will offer GPUs worldwide for GCE and Google Cloud Machine Learning users.”

GPUs in Google Cloud helps to focus on solving challenging computational problems while accessing GPU-equipped machines from anywhere “for a few hours or several weeks.” Up to 8 GPU dies can be attached per VM instance including custom machine types.

Google Cloud will offer AMD FirePro S9300 x2 as weel as NVIDIA Tesla P100 and K80 GPUs for deep learning, AI and HPC applications that require powerful computation and analysis.

gpus on google cloud

GPUs on Google Cloud

Google Cloud Machine Learning launched earlier this year already has a steady stream of new APIs, tools and services—now created a new group with a focus exclusively on delivering cloud-based machine learning solutions to all businesses.

In addtion following new additions are introduced:

A brand new Google Cloud Jobs API, which uses cloud machine learning and provides businesses with Google-strength capabilities to find, match and recommend relevant jobs to candidates is launched.

The Cloud Jobs API now available in a limited alpha, is intended for job boards, career sites and applicant tracking systems. .

To learn more, visit the Cloud Jobs API page.

In and effort to make Cloud Vision API affordable for everyone, Google has made improvements and reduce prices for Cloud Vision API by ~80%, as it now takes advantage of Google’s custom TPUs [custom ASIC built for machine learning, to improve performance and efficiency].

For example: the logo detection feature can identify millions of logos and label detection can identify an expanded number of entities, such as landmarks and objects in images.

Now offering Cloud Translation API (formerly Google Translate API) Premium to all partners, developers and businesses bringing the capabilities of recently launched Google Neural Machine Translation system (GNMT) that uses state-of-the-art training techniques and runs on TPUs to achieve some of the largest improvements for machine translation in the past decade.

The Premium edition is tailored for users who need precise, long-form translation services. While the Standard edition continues to offer translation in over 100 languages and price-performance ideal for short, real-time conversational text.

Additionally, price of the standard edition for higher usage volumes is decreased as well.

google cloud translation apis premium and standard edition

Google Cloud Translation APIs Premium and Standard Edition.

Cloud Natural Language API, a text analysis machine learning service is graduated to general availability, and has beed used by over 200 million people while in beta to store billions of notes and attachments.

The new features releasing with GA include:

  • Expanded entity recognition with increased accuracy to identify the names of things, such as people, companies, or locations in the text.
  • Granular sentiment analysis with expanded language support at the sentence level and not just within a document or record.
  • Syntax analysis with additional morphologies such as number, gender, person and tense, to improve coreference resolution required of advanced NLP tasks, writes google.

Update 12/02: Google Cloud Platform is now officially an IBM Eligible Public Cloud, meaning under IBM’s Bring Your Own Software License policy (BYOSL), customers using their existing licenses can run a range of IBM software SKUs on Google Compute Engine.

This applies to everything from middleware and DevOps products (Websphere, MQ Series, DataPower, Tivoli) to data and analytics offerings (DB2, Informix, Cloudant, Cognos, BigInsights).

Those who don’t have IBM licensing yet, can buy through either Passport Advantage or an authorized reseller.

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