Thursday, 21 November 2019

Accelerating data for NVIDIA GPUs

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These days, most AI and big data workloads need more compute power and memory than one node can provide. As both the number of computing nodes and the horsepower of processors and GPUs increases, so does the demand for I/O bandwidth. What was once a computing challenge can now become an I/O challenge.

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For those scaling up their AI workloads and teams, high-performance filesystems are being deployed because it addresses that I/O challenge. These deliver the bandwidth needed to feed the systems to keep them busy.

This week, NVIDIA announced a new solution–Magnum IO–that complements the capabilities of leading-edge data management systems such as IBM Spectrum Scale and helps address AI and big data analytics I/O challenges.

NVIDIA Magnum IO is a collection of software APIs and libraries to optimize storage and network I/O performance in multi-GPU, multi-node processing environments. NVIDIA developed Magnum IO in close collaboration with storage industry leaders, including IBM. The NVIDIA Magnum IO innovative software stack includes several NVIDIA GPUDirect technologies (Peer-to-Peer, RDMA, Storage, and Video) and communications APIs (NCCL, OpenMPI, and UCX). NVIDIA​ GPUDirect Storage is a key feature of Magnum IO, enabling a direct path between GPU memory and storage to improve system throughput and latency, therefore enhancing GPU and CPU utilization.

NVIDIA Magnum IO is designed to be a powerful complement to the IBM Spectrum Storage family. IBM Spectrum Scale, for example, was developed from the beginning for very high-performance environments. It incorporates support for Direct Memory Access technologies. Now, NVIDIA Magnum IO  is extending I/O technologies to speed NVIDIA GPU I/O.

For technology solution providers such as IBM and NVIDIA, the key is to integrate processors, GPUs, and appropriate software stacks into a unified platform designed specifically for AI. NVIDIA is also a major player in this space – 90 percent of accelerator-based systems incorporate NVIDIA GPUs for computation.

Recently, IBM and NVIDIA have been working together to develop modern IT infrastructure solutions that can help power AI well into the future. The synergies created by the IBM and NVIDIA collaboration have already been demonstrated at the largest scales. Currently, the two most powerful supercomputers on the planet – Summit at Oak Ridge and Sierra at Lawrence Livermore National Labs – are built from IBM Power processors, NVIDIA GPUs and IBM Storage. A key to these installations is the fact that they were assembled using only commercially available components. Leveraging this crucial ingredient, there are a range of solutions being offered by IBM and our Business Partners–from IBM supported versions of the complete stack to SuperPOD reference architectures featuring IBM Spectrum Scale and NVIDIA DGX systems.

Developing technology designed to increase data pipeline bandwidth and throughput is only part of the story. These solutions provide comprehensive reference architectures that incorporate a wide range of IBM Spectrum Storage family members, including IBM Cloud Object Storage for scalable data, IBM Spectrum Discover to manage and enhance metadata, and IBM Spectrum Protect to provide modern multicloud system security. The focus is on user productivity and support for the entire data pipeline.

The announcement of NVIDIA Magnum IO highlights the benefits of ecosystem collaboration to bring innovation to AI. As enterprises move rapidly toward adopting AI, they can do so with confidence and support of IBM Storage.


Magnum IO SC19: Accelerating data for NVIDIA GPUs with IBM Spectrum Scale

Source: ibm.com

Monday, 18 November 2019

My Strategy to Prepare for IBM Cognos Controller Developer (C2020-605) Certification Exam

About IBM Cognos Controller Developer Certification

IBM Cognos Controller is given with an integration component, Financial Analytics Publisher, that automates the process of obtaining data in near real-time from IBM Cognos Controller into IBM Cognos TM1. After the data is a source in IBM Cognos TM1, it can then be inserted as a data reference for IBM Cognos BI for enterprise reporting objectives.

The IBM Cognos Controller data in IBM Cognos TM1 is restored on a near real-time data through an incremental publishing process from the transactional controller database.

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The Financial Analytics Publisher element is added on top of the IBM Cognos Controller and manages a temporary storage area before populating an IBM Cognos TM1 cube. When configured, the IBM Cognos TM1 cube is continuously updated, and you can set how often the service frames run.

From the IBM Cognos TM1 cube, the IBM Cognos Controller data can be obtained by several reporting tools, including IBM Cognos studios.

IBM C2020-605 Exam Summary:

  • Name: IBM Certified Developer - Cognos 10 Controller
  • Code: C2020-605
  • Duration: 120 minutes
  • Exam Questions: 94
  • Passing Score: 65%
  • Exam Price: 200 USD

IBM C2020-605 Exam Topics:

  • Create Company Structures (5%)
  • Create Account Structures (12%)
  • Set up General Configuration (14%)
  • Enable Data Entry and Data Import (19%)
  • Create Journals and Closing Versions (5%)
  • Prepare for Currency Conversion (11%)
  • Configure the Control Tables (9%)
  • Eliminate and Reconcile Intercompany transactions and acquisitions (10%)
  • Consolidate a Group's Reported Values (5%)
  • Secure the Application and the Data (4%)
  • Create Reports to Analyze Data (6%)

Preparation Tips for IBM Cognos Controller Developer (C2020-605) Certification Exam

1. If You Can Not Do the Past Papers Ask Someone For Help

Study groups work well, given you do not think this will mean other people are doing your studying for you.

You have to go and study a subject or try an exam paper by yourself first, then meet together to explain your answers. Don’t work through the past exam questions in the group.


The attraction to let other people do the work is too strong. You require to learn to do it yourself.

2. Do Not Be Tired

If you have to wait up all night to do last minute revision, you have already failed. It does not work. You end up so tired in the exam you cannot work anything out. It might work for the examination in a year, but you would not be able to hold it up during the C2020-605 exam.

3. Eat Protein Before Long Exam

An exam is just as much a physical exercise as a race. Perhaps not quite as much, but you can not ignore your body if you want your brain to work at its best. Filling it full of sugar, or some energy drink just before will work fine for the first hour or so, but by the end of a C2020-605 exam, you will have run entirely out of energy. You require some food that will slowly release energy.

4. Get the Important Facts into Short-term Memory

In the last 24 hours, it is too late to try and get anything new. What you can do is read some facts into short-term memory. This is the time to go through the notes, looking at those critical points sections. If you have not already done it as part of your revision and you should have done it, write out a sheet with just the key facts.

5. Practice Tests

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