TGAC Unleashes DRAGEN to Accelerate Genomics Workflows

By John Russell

October 28, 2015

Accelerating genomics analysis remains one of the toughest challenges in life science research. All manner of optimizations are in use – disk streaming, optimized parallel files systems, algorithm tweaks, faster processors, and hardware accelerators, to name a few – all with varying results. Today, TGAC reported implementation of the first processor specifically designed to accelerate the full gamut NGS analysis workflows, Edico Genome’s DRAGEN system.

Initial evaluations have looked extremely promising. DRAGEN mapping against the ash tree genome was 177 times faster per processing core than TGAC’s local HPC systems, requiring only seven minutes instead of three hours on one of the larger datasets. Alignment runs on the rice genome that take approximately two hours on TGAC’s HPC servers took just three minutes using DRAGEN. Not surprisingly the TGAC folks are excited.

“At TGAC we see the DRAGEN dramatically improving our mapping thru variant-calling pipelines immediately. It uses optimized versions of standard tools such as algorithms for analyzing genomic data, including reference‐based mapping, aligning, sorting, deduplication and variant calling. We could easily replace many traditional HPC servers with the DRAGEN system saving both space and energy,” said project lead Dr Tim Stitt, also head of scientific computing at TGAC (The Genome Analysis Center, U.K. (description below)).

DRAGEN board 3The DRAGEN system is an FPGA-based approach; the DRAGEN Bio-IT Processor is integrated on a PCIe card and available in a pre-configured server that can be easily integrated into bioinformatics workflows. The highly reconfigurable FPGA provides hardware-accelerated implementations of BCL conversion, compression, mapping, alignment, sorting, duplicate marking, haplotype variant calling and joint genotyping.

Hardware acceleration, of course, isn’t new in bioinformatics. At one or another time there have been dedicated board-level and system level offerings from third parties. Convey Computer (now part of Micron), for example, introduced a ‘hybrid-core’ heterogeneous system, which used FPGAs and customized code to dramatically speed a variety of analysis tasks including BLAST and Graph analysis.

Moreover, sequencing centers are constantly fiddling with their systems to coax faster throughput. Early this year, blogger Richard Casey, a bioinformaticist at Colorado Statue University Next Generation Sequencing Core, reported achieving a 12X analysis speed-up using the new the Tesla K80, NVIDIA’s newest GPU in the Tesla series. (See HPCwire article, NVIDIA K80 GPU-System Speeds up Bioinformatics Tool 12X).

Said Stitt, “DRAGEN is the world’s first end-to-end platform for genomics – from BCL files in to annotated variant called files out. DRAGEN technology capitalizes on the availability of FPGAs in commodity servers that will be available on, for instance, Intel’s servers in the near future. This gives DRAGEN great scale and the technology can be deployed both locally onsite, close to a sequencing instrument, and also in the cloud.

Tim_STITT.TGAC.2“Convey’s product did not provide an end-to-end solution and only implemented small incremental steps of the pipeline. The Edico Genome engineering team that implemented and designed the architecture and algorithms for DRAGEN have previously worked on leading edge cell phone, telecommunication and data analytics chips. Updates and improvements to our platform and pipelines are done in a rapid and efficient way and does not take longer to update than traditional software updates,” said Stitt.

The DRAGEN system is engineered to keep the FPGA accelerators and CPUs busy. In order to do that the DRAGEN HW/SW is partitioned optimally and is highly scalable. IO access of the files fed to the DRAGEN is architected so as to avoid IO being the bottleneck. DRAGEN uses multiple high-end SSD drives in a RAID 0 configuration to maximize throughput in and out of disk. Further, DRAGEN on board memory has very large bandwidth that allows the DRAGEN FPGA to limit the IO interaction with the file system to a minimum.

Interestingly serendipity played a role in bringing DRAGEN to TGAC. “A member of our communications team picked up a press release introducing the DRAGEN system, explaining how it was reducing the analysis time (from mapping thru variant calling) for a human genome from 24 hours down to 20 minutes. This was a huge performance speedup and I was curious if it could be applied to non-human genomes as well,” said Stitt.

TGAC specialises in the sequencing and analysis of microbial, plant and animal genomes to advance a sustainable bioeconomy and protect the UK’s food security. With respect to the latter, it particularly focuses on the wheat genome.

Source: Shutterstock
Source: Shutterstock

“Since wheat is a staple diet for over 30% of the world’s population, we are focused on improving yields for an increasing population (estimates predict nine billion people worldwide by 2050) against the challenges of less space to grow wheat and heat, drought and pathogens that severely deplete wheat yield worldwide. By understanding the wheat genome we can help breeders overcome some of these obstacles. Unfortunately the wheat genome is five times bigger than the human genome and much more complex,” said Stitt.

Difficulty programming FPGAs has long been a stumbling block to wider adoption of the flexible technology. Stitt wondered how practical it would be to attempt to modify the DAGEN system for analysis of non-human genomes. Edico was also unsure initially, said Stitt, but was also willing to try.

“I provided them with an Ash Tree genome to test this out and after a couple of months they came back with the results of running on the DRAGEN. The fidelity of the results was comparable with those obtained on our local HPC cluster, yet it was much faster. Over the following months Edico engineers ran other test sets in-house for me including rice and horse genomes. Each time they had to adapt their pipelines slightly to handle the new genome but the performance results were very impressive.”

Once programmed, the system’s relative ease of use and flexible deployment were attractive features noted Stitt. The DRAGEN system can be housed close to the sequencing machines or in the Cloud. Users can interact with the system using a GUI or an API.

“I think we will be the first users to integrate the [DRAGEN] system within our existing HPC cluster as a scheduler resource, so users can target the system through a batch script like they would target a GPU or Xeon-Phi for instance. We will work closely with Edico Genome to implement this. We see the DRAGEN contributing significantly to mapping thru variant-calling workloads at TGAC, particularly for our strategic projects were time-to-solution is very important. This is where the DRAGEN gives us the edge over other approaches,” said Stitt.

DRAGEN-in-Front-of-Box-1030x686Edico is quite young, founded in 2013, but seems to be gaining attention. The DRAGEN system is proving faster than many traditional approaches that execute algorithmic implementations in software. In a recent study published in Genome Medicine, DRAGEN sped up analysis of a whole genome from 22.5 hours to 41 minutes, while also achieving sensitivity and specificity of 99.5 percent. Similar efficiency gains could make an enormous impact due to the high throughput of genomic data processed at TGAC, where sequence alignment is critical to many sequencing projects. The DRAGEN technology has also been shown to accurately analyze over 50 whole human genomes (from FASTQ to VCF) in less than a day.

“Our collaboration with TGAC, a powerhouse in genomics that is home to one of the largest computing hardware facilities in Europe, is a great example of the benefits DRAGEN holds for sequencing centers,” said Pieter von Rooyen, CEO, Edico.

About TGAC (Source: TGAC)
The Genome Analysis Centre (TGAC) is a world-class research institute focusing on the development of genomics and computational biology. TGAC is based within the Norwich Research Park and receives strategic funding from the Biotechnology and Biological Science Research Council (BBSRC). TGAC is one of eight institutes that receive strategic funding from BBSRC. TGAC operates a National Capability to promote the application of genomics and bioinformatics to advance bioscience research and innovation.Vertical Focus: HPC in BioIT

TGAC offers state of the art DNA sequencing facility, unique by its operation of multiple complementary technologies for data generation. The Institute is a UK hub for innovative Bioinformatics through research, analysis and interpretation of multiple, complex data sets. It hosts one of the largest computing hardware facilities dedicated to life science research in Europe. It is also actively involved in developing novel platforms to provide access to computational tools and processing capacity for multiple academic and industrial users and promoting applications of computational Bioscience. Additionally, the Institute offers a Training program through courses and workshops, and an Outreach program targeting schools, teachers and the general public through dialogue and science communication activities. www.tgac.ac.uk

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!

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips are available off the shelf, a concern raised at many recent Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announced its second fund targeting €200 million. The very idea th Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. In a way, Nvidia is the new Intel IDF, the hottest chip show Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in its cloud service.  Google claimed the CPU is based on cut Read more…

Computational Chemistry Needs To Be Sustainable, Too

April 8, 2024

A diverse group of computational chemists is encouraging the research community to embrace a sustainable software ecosystem. That's the message behind a recent perspective article published in the Journal of Chemical Read more…

U.S. 2024/25 Science Budgets Taking a Hit

April 8, 2024

In case you missed it, fiscal 2024/25 U.S. science budgets seem likely to take big hits despite Congressional talk of increased support, reports the American Institute of Physics (AIP) FYI policy tracking coverage. AIP F Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it Read more…

Computational Chemistry Needs To Be Sustainable, Too

April 8, 2024

A diverse group of computational chemists is encouraging the research community to embrace a sustainable software ecosystem. That's the message behind a recent Read more…

Hyperion Research: Eleven HPC Predictions for 2024

April 4, 2024

HPCwire is happy to announce a new series with Hyperion Research  - a fact-based market research firm focusing on the HPC market. In addition to providing mark Read more…

Google Making Major Changes in AI Operations to Pull in Cash from Gemini

April 4, 2024

Over the last week, Google has made some under-the-radar changes, including appointing a new leader for AI development, which suggests the company is taking its Read more…

Parallel Perspectives: HPC Internships Educate and Inspire 

April 4, 2024

As an undergraduate Sophomore at the University of Chicago, Joey Lin embarked on a journey to explore how an internship opportunity involving high-performanc 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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

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…

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…

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…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire