‘High Latency Times, We Have You Surrounded.’

By By Derrick Harris, Editor

February 4, 2008

It’s nearly impossible to overstate the importance of low-latency solutions in financial datacenters — whether for risk analysis, electronic trade processing, or anything in between — which explains GemStone Systems’ recent partnerships aimed at addressing the issue on two different fronts.

Made public in November, the first of these partnerships is a go-to-market arrangement with Azul Systems aimed at addressing the multiple needs of users who need to improve latency, scalability and performance in the face of ever-increasing data volumes. By approaching potential customers together and touting the benefits of running GemStone’s GemFire Enterprise Data Fabric on top of the Azul Compute Appliance, both companies expect to see increased interest in their solutions. GemFire lets users create the types of highly available in-memory data grids necessary for extreme transaction processing (XTP) environments and Azul’s Compute Appliances supply the memory — ranging from 48 to 768 cores and from 96GB to 768GB of memory.

According to Asad Ali, senior product marketing manager at GemStone, testing between the two companies has shown that uploading an existing Java application into the GemStone-Azul environment is simply a matter of changing a few parameters, but the results belie the ease of deployment. Hundreds of commodity machines, he said, can be consolidated into several Azul appliances, and the combination of the proximity of the data and application, the reduction in networking, and the data being in-memory drastically speeds data access. Additionally, noted Ali, Azul’s no-pause garbage collection means Java applications can experience performance and scale the likes of which they rarely see in other environments.

Sanjay Sadhu, vice president of business development at Azul, is equally optimistic about the partnership, saying that a joint GemStone-Azul platform is actually greater than the sum of its parts. The financial services industry, he said, has serious latency concerns — on top of scalability, simplicity and availability concerns — yet many customers, including some top banks, “are not aware of a solution to the pain.” Combining Azul’s performance benefits with GemFire’s data access benefits not only solves these problems, but actually opens up new markets for institutions in terms of the number of traders who can access the data, said Sadhu. Azul Appliances can handle the needs of multiple applications because of the systems’ built-in SLA management, and GemFire allows multiple applications to access the data simultaneously.

Sadhu said the GemStone and Azul have been seeing a lot of interest in the joint solution, with most of it (perhaps not surprisingly) coming from the financial sector and focused on the data caching aspect — a critical element of the growing XTP market. However, both Sadhu and Ali agree that other vertical markets definitely could stand to benefit. Sadhu cites telco as one potential market, while Ali notes they are seeing growth in e-commerce and online gaming, as well. XTP is extremely important in transaction-intensive Web applications, a point Ali said was driven home by the number of retail Web sites that went down over Thanksgiving weekend.

Aside from handling the requirements of extreme transactional environments, Sadhu said a GemStone-Azul platform also helps give shape to grid and distributed environments by putting the focus on the application instead of on managing the environment. He can’t say whether the software or the hardware leads the solution, but together, he summarized, the companies solve problems — from giving power to Java applications to minimizing datacenter cost and complexity — that appeal to all levels of decision-makers. “We do see our value prop to be in the eyes and ears of CIOs and the architects who are building the solutions,” said Sadhu.

More recently, GemStone announced a partnership with IBM and Intel (and, to a lesser degree, Cisco) meant to address the extreme low-latency needs of the electronic trading industry. Called GemCache, the joint solution consists of GemStone’s GemFire software, IBM’s BladeCenter HS21 and Intel Quad-Core Xeon processors. In multi-server environments, the solution has utilized Cisco InfiniBand switches. According to Gideon Low, principal architect for business development and alliances at GemStone, GemCache is a result of common customers asking the three vendors to create a tight solution that addresses the customers’ real-world needs.

In order to demonstrate GemCache’s real-world throughput and latency capabilities, the companies put it through a first-of-its-kind benchmark test conducted by the Securities Technology Analysis Center (STAC). The solution demonstrated zero-loss reliability and guaranteed messaging into the transaction. As far as numbers go, the official announcement of the benchmark testing states:

The benchmark results showed the best-of-breed solution was able to support latency of less than 1 millisecond (987 msec) at 6,000 orders per second, with full data replication using a two-server GemCache configuration. In the tests, GemCache was also able to deliver a mean latency of 519 microseconds at 6,000 orders per second with a single server without replication. Additionally, three active/active two-server clusters supported 18,000 orders per second with approximately 1 millisecond (1,017 msec) of end-to-end latency using six IBM blade servers.

Near- or sub-millisecond latency times are needed to stay competitive in the trading markets, says Low, “but at the same time, you’re expected to be rock-solid, bulletproof, and never fail as a system and never lose data.” The numbers clearly illustrate that GemCache meets the former requirement, but it is the latter that often gets ignored. With GemCache, however, Low says data loss is all but eliminated via synchronous copying, and he said that they actually tightened the constraints in the benchmark test beyond what most customers do in their datacenters. Even pulling the plug on the primary processing machine did not result in data loss or impact on external applications, save for minimal failover time, he explained. Previous generations of solutions generally are several milliseconds slower, added Low, and cannot combine scalability, throughput and low latency like GemCache, nor can they generally handle both the database and messaging tiers like GemCache does.

Peter Lankford, founder and director of STAC, said the kinds of latencies demonstrated by GemCache are “significant” to end-users with whom his firm has spoken — users who usually are looking at roundtrip latency times in the low tens of milliseconds but want to go lower. Even more significant, said Lankford, is that GemStone, IBM and Intel did not bypass functionality in order to achieve an impressive number, but instead tried to construct a realistic benchmark with no data loss. Although this is the first execution-related benchmark STAC has published, Lankford added that it has created a standards organization over the past few months “to get everyone on the same page,” and the GemCache benchmark is a step in the right direction.

As for what drives what in a solution like this, Low is more definite than his more diplomatic GemStone colleague Sadhu. While Low acknowledges that hardware advances have been tremendous, he firmly believes the biggest difference maker in solutions like GemCache is the software architecture. Trying to carry out electronic trading transactions would be drastically slower using a traditional disk-based database architecture, he explained, so the move to an in-memory environment is critical — although having fast hardware certainly doesn’t hurt.

Like the GemStone-Azul solution, GemCache is available and in production today, although the pieces must be purchased individually. However, said Low, the companies involved are working on plans to co-market and co-sell the complete solution. As for the differences between the two environments, Low, who had a big part in the early testing work with GemFire and the Azul appliances, explained that the major differentiators are latency times and the amount of data that can be managed. While a GemStone-Azul environment cannot match the latency times of GemCache, the former, is very good for caching and managing a couple of hundred gigabytes of data while maintaining a better-than-average latency rate. As a result, said Low, GemCache is ideal for carrying out electronic trade processing, whereas the GemStone-Azul platform is better for real-time risk management or other processes that require the ability to drill into large amounts of data very quickly.

Regardless of what a customer’s needs are, though, “[low latency] gets more and more important every day,” said STAC’s Lankford, “and the reason is that in this market, invention is the mother of necessity. As soon as somebody down the street deploys some new technology that decreases their latency, everybody else has to keep up or they start losing deals.” Any delinquencies in latency are only exacerbated by the ever-increasing volumes of data and transactions firms are facing, as well as by the reality that machines are doing so much more trading than people, he added. “Once you make the decisions in silicon instead of neurons, now you’re on a completely different timescale.”

Subscribe to HPCwire's Weekly Update!

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

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

Nvidia Appoints Andy Grant as EMEA Director of Supercomputing, Higher Education, and AI

March 22, 2024

Nvidia recently appointed Andy Grant as Director, Supercomputing, Higher Education, and AI for Europe, the Middle East, and Africa (EMEA). With over 25 years of high-performance computing (HPC) experience, Grant brings a Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire