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Misc

sparklyr.sedona: A sparklyr extension for analyzing geospatial data

We are excited to announce the availability of sparklyr.sedona, a sparklyr extension making geospatial functionalities of the Apache Sedona library easily accessible from R.

Categories
Misc

sparklyr.sedona: A sparklyr extension for analyzing geospatial data

We are excited to announce the availability of sparklyr.sedona, a sparklyr extension making geospatial functionalities of the Apache Sedona library easily accessible from R.

Categories
Misc

sparklyr.sedona: A sparklyr extension for analyzing geospatial data

We are excited to announce the availability of sparklyr.sedona, a sparklyr extension making geospatial functionalities of the Apache Sedona library easily accessible from R.

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Offsites

sparklyr.sedona: A sparklyr extension for analyzing geospatial data

We are excited to announce the availability of sparklyr.sedona, a sparklyr extension making geospatial functionalities of the Apache Sedona library easily accessible from R.

Categories
Misc

How can Machine Learning fit this dataset

How can Machine Learning fit this dataset

Hey everyone!

i was exploring this dataset and i’m thinking to add ML model.

the challenge is how can ML be useful here. what’s the feature that can i predict?
i’m thinking about the description feature and NLP.

so i share this to get your insights guys!.

https://preview.redd.it/psa52zc2lr971.png?width=1409&format=png&auto=webp&s=edf62f3eb47f25f7f513687cc711c554dd9eb465

submitted by /u/YassineHamdaoui
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Misc

The development of science and technology make people can work for other city at home

The development of science and technology make people can work for other city at home submitted by /u/lzever
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Misc

Setting up TensorFlow 2.5 with NVIDIA GPU Support on Ubuntu 20.04

Setting up TensorFlow 2.5 with NVIDIA GPU Support on Ubuntu 20.04 submitted by /u/TuxThePenguin
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Categories
Misc

NVIDIA Launches UK’s Most Powerful Supercomputer, for Research in AI and Healthcare

NVIDIA today officially launched Cambridge-1, the United Kingdom’s most powerful supercomputer, which will enable top scientists and healthcare experts to use the…

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Misc

NVIDIA Nsight Perf SDK v2021.1 Now Available

The NVIDIA Nsight Perf SDK is a graphics profiling toolbox for DirectX, Vulkan, and OpenGL, enabling you to collect GPU performance metrics directly from your application.

The Nsight Perf SDK v2021.1 public release is now available for download.

New features include:

  • Simplified APIs to measure GPU performance within your application, and generate HTML performance reports    .
  • Lower-level range profiling APIs, with utility libraries providing ease-of-use.
  • All of the above, usable in D3D11, D3D12, OpenGL, and Vulkan.
  • Samples illustrating usage in 3D, Compute, and Ray Tracing.

New: Ray Tracing Samples

Below is a screenshot of Microsoft’s Real Time Denoised Ambient Occlusion sample, containing Nsight Perf SDK instrumentation. Each render pass or phase of execution has been annotated to take a measurement.

From the DispatchRay call’s HTML report, the following tables show the shader’s pipeline utilization and latency reasons. Quickly spot the most utilized pipelines via the bar charts, and inspect the exact numbers of operations performed.

This sample is bundled with the Nsight Perf SDK, which you can download from the product page. To try this out yourself, simply open the sample’s solution file in Visual Studio, build, and run. Step-by-step instructions are included in the Getting Started Guide.  If you have any questions, don’t hesitate to reach out via the Nsight Perf Forum.

For more details on the Nsight Perf SDK, check out the product page.

We want to hear from you! If you have any questions or suggestions, feel free to post them in the Nsight Perf Forum.

Categories
Misc

NVIDIA Continues BlueField DPU/DOCA Momentum with the Release of DOCA 1.1

NVIDIA released the NVIDIA DOCA 1.1 software framework for NVIDIA BlueField DPUs, the world’s most advanced Data Processing Unit (DPU).

Today NVIDIA released the NVIDIA DOCA 1.1 software framework for NVIDIA BlueField DPUs, the world’s most advanced Data Processing Unit (DPU).  This latest release aims to continue the momentum of the DOCA early access program with additional DOCA SDK, Runtime, and Services to enable developers to accelerate the development of applications on the DPU.

DPUs are increasingly useful for offloading, accelerating, and isolating networking functions and virtualized resources. Modern workload demands that impose too much networking overhead on the CPU cores provide tremendous motivation to adopt DPUs in every host. DPUs can handle all this virtualization (Open vSwitch (OVS), SR-IOV, RDMA) faster and more efficiently than standard CPUs. In addition, DPUs provide the benefit of security and operational isolation by running separately from the main CPU. The DPU can detect and block malicious behavior without requiring involvement from the CPU or host operating system.

DOCA is the key to unlocking the potential of the DPU. DOCA enables application developers and NVIDIA technology partners to accelerate delivery of services running on the DPU residing in every data center node. The DPU creates an isolated and secure services domain for networking, security, storage, and infrastructure management. 

The DOCA 1.1 release builds on the momentum of DOCA 1.0 and includes the following updates:

  • DOCA FLOW-LIB for accelerated Gateway capabilities that enable interoperability between discrete networks
  • DOCA FLOW example applications for URL and DNS filtering and forwarder function
  • Acceleration of Stateful Flow Table (SFT) for connection tracking
  • Accelerations of Regular Expression (RegEx) for pattern matching with DPI Lib
  • DOCA Runtime for x86 is introduced to enable applications running in x86 to be accelerated – while not necessarily completely offloaded – to the DPU

According to a recently published whitepaper from Bob Wheeler, Principle Analyst at The Linley Group, “The FLOW-Gateway library implements a hardware accelerated gateway, building on the data path’s SFT. Compared with the DPDK’s generic flow API (rte_flow), the library provides higher-level abstraction for gateway applications that filter and distribute network traffic. Similarly, the Deep Packet Inspection (DPI) library combines SFT and RegEx acceleration, exposing a high-level API to the application layer. It enables unanchored searches of packet payloads against a compiled signature database.”

You can read more about DOCA in Wheeler’s whitepaper, “DPU-Based Hardware Acceleration: A software Perspective.”

What is in the DOCA Stack?

Below is a high-level view of the DOCA stack:

There are three main components of DOCA: drivers, libraries, and services. Each of these runs on the DPU – including BlueField and BlueField-X (a tightly coupled DPU-GPU converged solution). DOCA also includes reference applications available or being developed and deployed on the DPU, including Networking, Security, Storage, HPC/AI, Telco, and Media.  All of these applications can be offloaded, accelerated, and Isolated from the CPU to dramatically improve performance and increase efficiency, enabling data center transformation into state-of-the-art virtual private clouds with public cloud scalability that are accelerated, fully programmable, and secure.

For a detailed description of each of the DOCA components, watch the recent GTC 21 session by Ami Badani and Ariel Kit of NVIDIA titled, “Program Data Center Infrastructure Acceleration with the Release of DOCA and the Latest DPU Software.”

Summary of DOCA Benefits

DOCA aids the developer journey to realize NVIDIA’s vision of an accelerated Data Center that includes the DPU as the third pillar in conjunction with the CPU and GPU. Through DOCA, NVIDIA is enabling access to all DPU features while also simplifying the creation of new applications or integrating existing applications on the DPU. DOCA offers several benefits as noted below:

  • DOCA simplifies the development and deployment process for infrastructure applications and functions that use the DPU, allowing for faster time-to-market for applications.
  • Unified access to all the DPU features: Accelerates development by putting all needed resources in one place to avoid tracking down scattered and disparate tools.
  • Higher-level libraries with an abstraction layer on top of low-level DPU APIs: Enables partners to integrate at a high level for fast, easy, and high-performance development, or integrate at a lower level for more fine-grained control.
  • Forward/backward compatibility: Developing with DOCA means that apps run seamlessly on future versions of the BlueField DPU while gaining higher performance and scale.
  • DPU provisioning and deployment of containerized services: DOCA includes tools to simplify DPU setup, provisioning, and services orchestration.
  • DOCA development container and SDK manager for enhanced developer’s experience enabling you to create your most innovative application on any system with a containerized developer environment and easily update your DPU card and port your runtime application to run in the DPU Arm cores using the SDK manager.

Beyond the DOCA 1.1 release, NVIDIA will continue to add to the DOCA libraries, drivers, and services with application examples to enable application development for a wide range of Networking, Storage, Security, and Infrastructure Management use cases. 

In addition, NVIDIA will continue to drive momentum with joint solutions from our ecosystem partners, the first of which will soon be announced. The ecosystem of DOCA/DPU partners and Early Access developers is growing rapidly, enabling customers access to best-in-class network, security, and storage solutions from industry leaders today. 

Try DOCA Today

You can experience DOCA today with the BlueField DPU software package, which includes DOCA runtime accelerated libraries for networking, storage, and security. The libraries help you program your data center infrastructure running on the DPU.

The DOCA Early Access program is open now for submissions. To receive news and updates about DOCA or to become an early access member/partner, register on the DOCA page.

If you are interested in learning more about DOCA, please find several DOCA resources below:

DOCA product page
Early Access Registration page
DOCA Getting Started page (Requires registration)
NVIDIA DOCA Developer Forum
Bob Wheeler, The Linley Group whitepaper: DPU-Based Hardware Acceleration: A Software Perspective
DOCA On-Demand Session: Program Data Center Infrastructure Acceleration with the Release of DOCA and the Latest DPU Software

DOCA and BlueField DPU Developer Blog posts: