NVIDIA Tesla Matchoff: K40 Versus the K20X

By Tiffany Trader

November 27, 2013

The digital ink has barely dried on NVIDIA’s K40 GPU announcement, but the engineering team over at Xcelerit have already gotten their hands on one. Xcelerit, which runs a business optimizing codes for accelerators, is also becoming known as the go-to benchmarking resource for the latest accelerators and multicore chips.

Compared to its previous high-end Kepler, the K20X, the NVIDIA Tesla K40 touts more memory, higher clock rates, and more CUDA cores. But how do these specs pay off in terms of actual performance improvements for real-world financial applications? This is what the Xcelerit team wanted to know, so they arranged a face-off between the K40 and the K20X using the Monte-Carlo LIBOR swaption portfolio pricer as the yardstick.

The hardware comparison breakdown is illustrated with this table:

Tesla K20X Tesla K40
SMX 14 15
CUDA Cores 2,688 2,880
Memory 6 GB 12 GB
Core Frequency 732 MHz 745 MHz
Max. Frequency 784 MHz 875 MHz
Memory Bandwidth 250 GB/s 288 GB/s

 

Jörg Lotze, technical lead and co-founder at Xcelerit, explains that aside from the obvious differences in clock speeds, core count and memory, the most significant enhancement to the K40 is a GPU Boost mode that turns up the frequency on those CUDA cores. Up to 17 percent higher frequency is possible as long as the device stays within its specified thermal envelope. Exceeding that limit will cause the clock to be automatically throttled. The K20X only allows a small clock boost of 7 precent.

The benchmark employs Monte-Carlo LIBOR swaption portfolio pricing. This is a common financial algorithm used to price a portfolio of LIBOR swaptions. It involves the simulation of thousands of possible future development paths for the LIBOR interest rate. For each of these paths, the value of the swaption portfolio is computed by applying a portfolio payoff function. Both the final portfolio value and an interest rate sensitivity value are obtained by computing the mean of all per-path values.

For a high number of paths, the algorithm becomes compute bound, creating a scenario where the additional cores and higher clock speeds should create a significant performance boost.

The application was implemented with the Xcelerit software on two systems, each outfitted with dual Intel Xeon E5s and the target GPU.

From the blog:

We measured the computation times for the Monte-Carlo LIBOR swaption portfolio pricer on one GPU of each system, pricing a portfolio of 15 swaptions over 80 time steps and using varying numbers of Monte-Carlo paths. The run time of the full algorithm – including random number generation, data transfers, core computation, and reduction – is compared for single and double precision in the graph below. All these computation steps are running on the GPU, so the difference in the used CPUs does not affect the benchmark results.

With the default clock frequency settings, the K40 returned a speedup of between 1.1 and 1.2 times. When the team tested the application with frequency dialed up all the way, the K40 performance boost was even more pronounced, between 1.2 and 1.25 times higher.

The Xcelerit team created this chart with several notable points of comparison:

Paths Speedup (def. clock, single) Speedup (def. clock, double) Speedup (max. clock, single) Speedup (max. clock, double)
16K 1.15x 1.17x 1.21x 1.21x
256K 1.15x 1.17x 1.21x 1.26x
1024K 1.15x 1.18x 1.22x 1.28x

 
The benchmarking results show that the K40 provides a significant performance improvement for this real-world financial application, up to 1.28x with the higher clock speed enabled. The Xcelerit rep notes that the speedup is pretty constant across number of paths, too, indicating that even small loads benefit from the new GPU. “Together with the doubled memory capacity, this makes a strong case for the Tesla K40 GPU,” he writes.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Nvidia Debuts Turing Architecture, Focusing on Real-Time Ray Tracing

August 16, 2018

From the SIGGRAPH professional graphics conference in Vancouver this week, Nvidia CEO Jensen Huang unveiled Turing, the company's next-gen GPU platform that introduces new RT Cores to accelerate ray tracing and new Tenso Read more…

By Tiffany Trader

HPC Coding: The Power of L(o)osing Control

August 16, 2018

Exascale roadmaps, exascale projects and exascale lobbyists ask, on-again-off-again, for a fundamental rewrite of major code building blocks. Otherwise, so they claim, codes will not scale up. Naturally, some exascale pr Read more…

By Tobias Weinzierl

STAQ(ing) the Quantum Computing Deck

August 16, 2018

Quantum computers – at least for now – remain noisy. That’s another way of saying unreliable and in diverse ways that often depend on the specific quantum technology used. One idea is to mitigate noisiness and perh Read more…

By John Russell

HPE Extreme Performance Solutions

Introducing the First Integrated System Management Software for HPC Clusters from HPE

How do you manage your complex, growing cluster environments? Answer that big challenge with the new HPC cluster management solution: HPE Performance Cluster Manager. Read more…

IBM Accelerated Insights

Super Problem Solving

You might think that tackling the world’s toughest problems is a job only for superheroes, but at special places such as the Oak Ridge National Laboratory, supercomputers are the real heroes. Read more…

NREL ‘Eagle’ Supercomputer to Advance Energy Tech R&D

August 14, 2018

The U.S. Department of Energy (DOE) National Renewable Energy Laboratory (NREL) has contracted with Hewlett Packard Enterprise (HPE) for a new 8-petaflops (peak) supercomputer that will be used to advance early-stage R&a Read more…

By Tiffany Trader

STAQ(ing) the Quantum Computing Deck

August 16, 2018

Quantum computers – at least for now – remain noisy. That’s another way of saying unreliable and in diverse ways that often depend on the specific quantum Read more…

By John Russell

NREL ‘Eagle’ Supercomputer to Advance Energy Tech R&D

August 14, 2018

The U.S. Department of Energy (DOE) National Renewable Energy Laboratory (NREL) has contracted with Hewlett Packard Enterprise (HPE) for a new 8-petaflops (peak Read more…

By Tiffany Trader

CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

August 14, 2018

An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learni Read more…

By Rob Farber

Intel Announces Cooper Lake, Advances AI Strategy

August 9, 2018

Intel's chief datacenter exec Navin Shenoy kicked off the company's Data-Centric Innovation Summit Wednesday, the day-long program devoted to Intel's datacenter Read more…

By Tiffany Trader

SLATE Update: Making Math Libraries Exascale-ready

August 9, 2018

Practically-speaking, achieving exascale computing requires enabling HPC software to effectively use accelerators – mostly GPUs at present – and that remain Read more…

By John Russell

Summertime in Washington: Some Unexpected Advanced Computing News

August 8, 2018

Summertime in Washington DC is known for its heat and humidity. That is why most people get away to either the mountains or the seashore and things slow down. H Read more…

By Alex R. Larzelere

NSF Invests $15 Million in Quantum STAQ

August 7, 2018

Quantum computing development is in full ascent as global backers aim to transcend the limitations of classical computing by leveraging the magical-seeming prop Read more…

By Tiffany Trader

By the Numbers: Cray Would Like Exascale to Be the Icing on the Cake

August 1, 2018

On its earnings call held for investors yesterday, Cray gave an accounting for its latest quarterly financials, offered future guidance and provided an update o Read more…

By Tiffany Trader

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17

Altair

AMD @ SC17

AMD

ASRock Rack @ SC17

ASRock Rack

CEJN @ SC17

CEJN

DDN Storage @ SC17

DDN Storage

Huawei @ SC17

Huawei

IBM @ SC17

IBM

IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17

Intel

Lenovo @ SC17

Lenovo

Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17

Microsoft

Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17

Supericro

Tyan @ SC17

Tyan

Univa @ SC17

Univa

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This