Tesla Personal Super Computer

Priya ManikpuriM.Sc.(CS)-I Sem-IIShri.Shivaji Science college, Nagpur

Contents1. Introduction

2. Features

3. GPU Computing

4. CUDA parallel architecture and programming model.

5. Tesla C1060 Specifications and architecture.

6. Advantaged and Disadvantages

7. Future Scope

8. Conclusion

IntroductionGPU-based desktop computer

backed by NVIDIA

built by Dell, Lenovo and other companies

NVIDIA's CUDA parallel computing architecture

933 Gigaflops peak performance

250 times faster than standard PCs

Tesla certified system, Windows XP(32 –bit) and Linux (64-bit and 32-bit )are the supported platforms.

FeaturesMulti-GPU Computing

Massively Multi-threaded Computing Architecture

4 GB High-Speed Memory per GPU

High Speed , PCI-Express Gen 2.0 Data Transfer

64-bit ALUs for Double-Precision Math

GPU ComputingGPU computing is the use of a GPU(graphics processing

unit) to do general-purpose scientific and engineering computing.

The model for GPU computing is to use a CPU and GPU together in a heterogeneous computing model.

CUDA Parallel Architecture and Programming Model

CUDA stands for Compute Unified Device Architecture

Developed by NVIDIA to help code for GPUs (specifically their GPUs)

An extension of C and C++

CUDA offers a data parallel programming model

Tesla C1060 Computing Processor• GPU

-Number of processor cores: 240 -Processor core clock: 1.296 GHz -Max Power Consumption:187.8 W  

• Memory -Total Dedicated Memory: 4 GB -Memory speed :800 MHz -Memory Interface :512-bit GDDR3 -Memory Bandwidth: 102 GB/sec

•  External Connectors: None

• Internal Connectors and Headers: -One 6-pin PCI Express power connector -One 8-pin PCI Express power connector -4-pin fan connector

At the heart of the new Tesla personal supercomputer are three or four NVIDIA Tesla C1060 computing processors.

The application start at the host side(the CPU) which communicates with the device side(the GPU)through PCI-Express x16(bus).

NVIDIA Tesla - Architecture

Tesla C1060 comprises of 30 Streaming multiprocessors(SMs).

The SM is the processing unit, and it is unified graphics and computing multiprocessor.

Each SM is comprised of eight scalar processors (SPs) , 16-kb of shared chip memory, and 16,884 32-bit registers.

Each SM has two single-precision transcendental (Special Functions ,SF) units to carry out transcendental functions.

NVIDIA Tesla - Components

NVIDIA Tesla - Components

Texture Unit – Processes one group of threads per cycle, optimized for texture computations

Raster operations processor (ROP) - Paired with a specific memory

partition and texture/processor cluster - Supports an interconnect with both DDR2 and GDDR3 memory for up to 16 GB/s bandwidth - Processor is used to aid in anti

aliasing

• Warp Capability: Each streaming multiprocessor handles 24 warps, or 768 threads.

 • Memory Access:

 

Data Flow and Memory

• Memory and Interconnect:

Bus of 384 pins with 6 independent partitions (Means many possible connections)

  Use GDDR3 RAM, which has much higher bandwidth,

though requires more power, than DDR DRAM 

Memory traffic within the chip goes through a specific component of the hardware that combines the various components together (the ROP)

Data Flow and Memory

Advantages and DisadvantagesAdvantages:

Your own Supercomputer Designed for Office Use Solve Large-scale Problems using Multiple GPUs They can be used in medical applications for processing brain and

body scans, resulting in faster diagnosis.

Disadvantages:

Overheating: If a GPU hits the maximum temperature, the driver throttles down performance and shutdown the system.

CUDA does not support the full C standard, as it runs host code through a C++ compiler, which makes some valid C (but invalid C++) code fail to compile.

Future Scope

Although at £4,000 and £8,000 it is beyond the reach of most consumers, the high-performance processor could become invaluable to universities and medical institutions.

The NVIDIA’s Tesla computer could prove invaluable to medical researchers and accelerate the discovery cures for diseases.

With the massively parallel architecture of the GPU, scientists and engineers can get a quantum jump in performance and continue to advance the pace of their work, guiding us to faster discovery in drug research, weather modeling, oil and gas exploration, computational finance, and more

ConclusionThe technology represents a great leap forward in the

history of computing.

The new computers make innovative use of graphics processing units

The Tesla Personal Supercomputer doesn't make supercomputing clusters obsolete but it's a major breakthrough for millions of researchers who can take advantage of the huge heterogeneous computing power of this system

These supercomputers can improve the time it takes to process information by 1,000 times.

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