TESLA K40 ACCELERATE COMPUTING FOR LARGE DATA SETS

0

1

2

3

4

5

CPU K20X K40

ns/day  

Tesla K40 FASTER

1.4 TF| 2880 Cores | 288 GB/s

AMBER Benchmark: SPFP-Nucleosome CPU: Dual E5-2687W @ 3.10GHz, 64GB System Memory, CentOS 6.2, GPU systems: Single Tesla K20X or Single Tesla K40

AMBER Benchmark

SMARTER Unlock Extra Performance

Using Power Headroom

LARGER 2x Memory Enables More

Apps

6GB

Fluid Dynamics

Seismic Analysis

Rendering

12GB

10.29x

10.23x

8.67x

8.12x

1.66x

0 2 4 6 8 10 12

SPECFEM3D

QMCPACK 4x4x1

AMBER - SPFP-Cellulose_production_NPT

Chroma

ANSYS 14 SMP-V14sp-4

Physics CHROMA

Earth Science SPECFEM3D

Structural Mechanics ANSYS

Molecular Dynamics AMBER

Material Science QMCPACK

Tesla K40 : Acceleration for Large Problems

E5-2687W @ 3.10GHz Tesla K20X

Tesla K40 3

Bigger Challenges – Less Time

M&E More complex scenes,

Accelerates color grading

Graph Analytics Accelerate larger graphs

Neural Networks Larger training sets

Quantum Chemistry Larger problems, more

acceleration

Molecular Dynamics Larger problems, more

acceleration

Bioinformatics Newer algorithms, apps

Material Science Larger ion/electron systems

CFD Larger models, higher

throughput

High Energy Physics More advanced event triggers

Video Frame Rate Conversion

3D Rendering Transcoding and

Encoding broadcast video

Color grading for film and

video

Tesla K40 in Media and Entertianment Creation Distribution

1 Billion Tweets

Faster Decisions

Live Streaming and Analysis

Tesla K40 : Interactive and Real-time Analysis

To Learn more: Register for map-D Webinar on 29th Jan @ 9am PST

8 Tesla K40

0

50

100

150

200

Boar

d Po

wer

(W

atts

) Avg GPU Power in Watts for Real Applications on K20X

4

235W

Power Envelope

Power headroom to higher Performance

GPU Boost on Tesla K40

Base Clock

Workload # 1 Worst case Reference App

235W

Boost Clock #1

Workload # 2 E.g. AMBER

235W

Boost Clock #2

Workload # 3 E.g. ANSYS Fluent

235W

Convert Power Headroom to Higher Performance

5

810Mhz

745Mhz

875Mhz

1.40

1.27 1.23 1.27 1.26 1.28 1.25

1.07

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

ANSYS 14 SMP-V14sp-4 LAMMPS-EAM NAMD 2.9-APOA1 AMBER-SPFP-Nucleosome LSMS-Fe32 QMCPACK 3x3x1 CUBLAS DGEMM

K20X K40@base K40 @ boost

Tesla K40 Performance Relative to Tesla K20X

Real Apps Run Up to 1.4x faster with GPU Boost

ANSYS LAMMPS-EAM NAMD 2.9 APOA1

AMBER-SPFP-Nucleosome

LSMS-Fe32 QMCPACK 3x3x1

CUBLAS DGEMM

6

Non-Tesla

Compute Workload Behavior with GPU Boost

GPU Clock

Automatic clock switching

Default @ Shipping   Boost Base

Preset Options   Lock to base clock 3 Levels: Base, Boost1 or Boost2

Boost Interface Control Panel NV-SMI, NVML

Target duration for boost clocks   ~50% of run-time

100% of workload run time Must-have for HPC workload

Boost Clock # 1

Boost Clock # 2

Tesla K40

Deterministic Clocks

Base Clock # 1

Using GPU Boost on Tesla K40

View the clocks

nvidia-smi -q –d CLOCK,SUPPORTED_CLOCKS

Set the Boost clocks

nvidia-smi -ac <MEM clock, Graphics clock>

Boost all 2880 Cores

End User selects the clocks

Higher memory b/w

GPU GPU

Host GPU

Customer Feedback on K40 w/GPU Boost

17% Faster 13% Faster 11% Faster

http://www.eyesopen.com/fastrocs

http://blog.xcelerit.com/benchmarks-nvidia-tesla-k40-vs-k20x-gpu/

K40 w/GPU Boost 40% higher perf

*Tesla K40 Performance Relative to Tesla K20X

Tesla Resources

!   Want to know more about Tesla Products http://www.nvidia.com/object/tesla-servers.html http://www.nvidia.com/object/tesla-workstations.html

!   Need help on using GPU Boost on Tesla K40 http://www.nvidia.com/object/tesla_product_literature.html

!   Product details, specs, etc.

http://www.nvidia.com/object/tesla_product_literature.html

!   Where to buy http://www.nvidia.com/object/where-to-buy-tesla.html

1.  Sign up for FREE GPU Test Drive visit: http://www.Nvidia.com/GPUTestDrive

2.  Accelerate your apps on latest K40 GPUs

3.  Tell us how K40 and GPU Boost worked for you

Test Drive the World’s Fastest GPU

Upcoming GTC Express Webinars

January 29: map-D: A GPU Database for Real-time Dig Data Analytics and Interactive Visualization

January 30: Debugging CUDA Fortran using Allinea DDT

February 5: OpenMM - Accelerating and Customizing Molecular Dynamic Simulations on GPUs

February 25: Using GPUs to Supercharge Visualization and Analysis of Molecular Dynamics Simulations with VMD

Register at www.gputechconf.com/gtcexpress

GTC 2014 Registration is Open Hundreds of sessions in the areas of

§  Science and research

§  Professional graphics

§  Mobile computing

§  Automotive applications

§  Game development

§  Cloud computing

Register with GM20EXP for 20% discount

www.gputechconf.com