• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer
Hardware Secrets

Hardware Secrets

Uncomplicating the complicated

  • Case
  • Cooling
  • Memory
  • Mobile
    • Laptops
    • Smartphones
    • Tablets
  • Motherboard
  • Networking
  • Other
    • Audio
    • Cameras
    • Consumer Electronics
    • Desktops
    • Museum
    • Software
    • Tradeshows & Events
  • Peripherals
    • Headset
    • Keyboard
    • Mouse
    • Printers
  • Power
  • Storage
  • Video

NVIDIA Tesla Technology

Everything you need to know about Tesla, a series of “video cards” from NVIDIA that are used to process regular programs and not video under a concept called GPGPU.

Home » NVIDIA Tesla Technology

Introduction

Contents

  • 1. Introduction
  • 2. Tesla S870
  • 3. Tesla S870 In Action

With the processing power of GPUs (i.e., the graphics chip located on the video card) increasing everyday – to the point that they are more powerful than regular CPUs for math calculations – it’s been discussed for quite some time now if GPUs couldn’t be used as a CPU for processing regular programs. The idea, known as GPGPU (General-Purpose Computation on GPUs), is to throw to the GPU calculations that would otherwise be done by the CPU in order to increase performance.

The problem is how to do this, as a programmer would have to know how to program to a specific GPU in order to make a program that could use the system GPU, and this program wouldn’t work with a different GPU.

To solve this issue NVIDIA launched a free C compiler to their GeForce 8800 series, called CUDA. With CUDA any programmer can easily compile their programs written in C to use the power of the system GPU to process their program.

Going one step further, NVIDIA launched a series of “video cards” called Tesla. These “video cards” feature GeForce 8800 GPUs but they do not produce video: they are targeted to be used as CPUs, processing programs. In this article we will tell you everything you need to know about Tesla, including a lot of pictures of Tesla solutions.

These programs must be compiled with CUDA, of course. So regular users won’t benefit this technology, i.e., don’t think that by installing one of these cards on your PC your processing performance will automatically increase.

Any kind of heavy-calculation program that does a lot of things in parallel can be benefited from the use of GPGPU – if they are compiled to use the GPU, of course. This includes mostly simulations (physics, financial, medical, biological and chemical, for example).

One very interesting thing about CUDA is that you don’t need to have a Tesla card installed to use it. So a programmer can buy any video card from the GeForce 8800 series and try it out to see if using the GPU instead of the CPU will in fact improve the performance of the application that is being written. If it works out fine, then the programmer can think of buying a more power system, namely a Tesla solution.

So far NVIDIA has launched three Tesla products:  a basic card, called C870, which is a GeForce 8800 video card but without a video output. The “C” on its name stands for “card.” This card has 1.5 GB of memory and has a math processing performance of 500 GFLOPS (billions of floating-point operations per second). Using a standard PCI Express x16 connector this card can be installed on any desktop computer.

NVIDIA Tesla C870Figure 1: Tesla C870 card.

NVIDIA Tesla C870Figure 2: Notice how this card doesn’t have a video output.

This basic card is the building block for the other two Tesla products available: D870 and S870.

D870 – where the “D” on its name stands for “Desktop” – is a small external case containing two C870 cards, so the processing power of this solution is of 1 TFLOP (trillion of floating-point of operations per second). This case is connected to the main PC through a cable, which is basically an expansion of the PCI Express bus.

NVIDIA Tesla D870Figure 3: The small case is the Tesla D870, which contains two C870 cards.

Then we have the most high-end model, Tesla S870, which holds four C870 cards inside. We will talk about this product in the next page.

Continue: Tesla S870

CPU Articles

Primary Sidebar

As a participant in the Amazon Services LLC Associates Program, this site may earn from qualifying purchases. We may also earn commissions on purchases from other retail websites.

audio connectors on a motherboard (right) and ethernet + usb connectors (left)

How On-Board Audio Works

Learn how the sound card that comes embedded on your motherboard works.

How To Connect Your PC to Your Home Stereo or Home Theater

Learn how to hook your PC to your stereo or receiver in order to enhance you audio experience while playing games, watching videos, listening to music or even editing audio.

motherboard

Which is the best motherboard for Coffee Lake CPUs?

We compared seven different motherboards for Intel eighth-gen (Coffee Lake) CPUs, to help you to choose which one is the best for you. Check it out!

RAM Install

Does more RAM make difference in gaming performance?

Does installing more RAM in your computer improves gaming performance? We tested some recent games with 4 GiB, 8 GiB, and 16 GiB to find out. Check it out!

How to Refill Epson Cartridges

Learn how to reset the Epson cartridge chip, allowing you to refill the cartridge.

Footer

For Performance

  • PCI Express 3.0 vs. 2.0: Is There a Gaming Performance Gain?
  • Does dual-channel memory make difference on integrated video performance?
  • Overclocking Pros and Cons
  • All Core i7 Models
  • Understanding RAM Timings

Everything you need to know

  • Everything You Need to Know About the Dual-, Triple-, and Quad-Channel Memory Architectures
  • Everything You Need to Know About the SPDIF Connection
  • Everything You Need to Know About the Intel Virtualization Technology
  • Everything You Need to Know About the CPU C-States Power Saving Modes

Follow Us

Follow us on Facebook Follow us on Twitter Follow us on Instagram

Copyright © 2022 · All rights reserved - Hardwaresecrets.com
About Us · Privacy Policy · Contact