FPGA-Accelerated Search Heads for Mainstream

By Tiffany Trader

March 10, 2015

With data volumes now outpacing Moore’s Law, there is a move to look beyond conventional hardware and software tools. Accelerators like GPUs and the Intel MIC architecture have extended performance goals for many HPC-class workloads. Although field-programmable gate arrays (FPGAs) have not seen the same level of adoption for traditional HPC workloads, a subset of big data applications have proved a good fit for the processor type.

The area where FPGAs have shined brightest is in search-based applications. Most notably, Microsoft is deploying FPGA-accelerated nodes for its Bing service and Asian Web giant Baidu has implemented a similar approach for pattern and image recognition.

Now we are seeing the debut of an FPGA-based appliance that is accelerating select analytics workloads and giving Hadoop and Spark clusters a run for their money. Ryft, a company that has been serving the government sector for over a decade, is jumping into the commercial analytics space with the deployment of Ryft ONE, a 1U analytics appliance that combines Xilinx FPGAs, twin parallel server backplanes and up to 48 TB of SSD-based storage with custom software primitives that hide the underlying hardware complexity. According to company benchmarks, the Ryft ONE platform can analyze data at speeds up to and exceeding 10 Gigabytes per second, some 100 to 200 times faster than the fastest 4 core CPU/15 GB RAM servers.

Bill Dentinger, vice president of products for Ryft, explains that they are targeting customer applications that require real-time insights from both streaming and historical data sets, in many cases simultaneously. After ten years of working on complex data sets with the government, Ryft drew from that experience to create a purpose-built solution that looks like a general-purpose Linux server but acts like a high-performance computer.

Pat McGarry, vice president of engineering, says Ryft One was designed to overcome the speed and performance bottlenecks of traditional x86 clusters. Each 1U box has eight drives and each one can house six off-the-shelf solid state drives for a total of 48 hot-swappable drives, providing up to 48 TB of SSD storage. The SSDs are RAIDed together in hardware. Data is ingested with dual 10GE cards.

Behind the front-end storage piece is Ryft’s secret sauce, a set of fundamental logic that is built into the Ryft Analytics Cortex (RAC) aimed at solving specific problems. McGarry explains that instead of using sequential processors, like x86, ARM, DSPs and the like, they implemented systolic arrays in an FPGA fabric, a massively parallel bitwise computing architecture. The move to this non von Neumann model is where Ryft differentiates itself.

While FPGAs lack the ease of programmability and familiarity of x86 Linux clusters, the use of hard coded primitives gets around these limitations by extracting away the internal complexities, using a standard C-language API to invoke a function. Ryft is launching with three primitives – search, fuzzy search, and term frequency operations (the equivalent of word count) – with plans to expand its library of prebuilt algorithm components in accordance with customer and market demands.

The initial custom software primitives are designed to tackle specific analytics workloads in areas where there is a requirement to find and match strings of text at lightening speed. Machine learning, fraud detection and gene sequencing are areas where they expect the platform to have the most impact initially.

When it comes to benchmarking results, McGarry reveals that a 1U Ryft box significantly outperforms quad-core x86 servers, as detailed in the following chart:

RyftOneBenchmarks
RyftOneBenchmarksnote

Furthermore by replacing hundreds of vanilla servers, the appliance reduces maintenance and operational costs by up to 70 percent.

If customers need more than one box, a sharding approach can be used to scale the system out, but the company says that what they are seeing is that most of their customers are not maxing out storage. They are running into data sizes in the realm of lower terabytes, with very few above 20 terabytes, outside of certain government needs.

Hosted and on-premise versions of Ryft One will be available in early Q2. The first-year cost of $200,000 includes an $80,000 integration fee. Thereafter, the price drops to $120,000 a year.

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