SOLUTION BRIEF

SambaNova DataScale®
for Science
Accelerate AI for Science workloads
to make more discoveries faster1

SAMBANOVA DATASCALE FOR SCIENCEWorld record performance to power worldchanging research
The world has entered a new era of AI, powered by foundation
models and state-of-the-art deep learning. Foundation models
make up the next generation of large scale models which aretransforming what is possible with AI and they are enablingorganizations to achieve new and exciting discoveries acrossnumerous areas of research, including true resolution medical
image analysis, large language models for science, andmulti-physics simulation workloads. While the potential for using
foundation models and deep learning to accelerate these
discoveries is immense, these state-of-the-art models come with
their own training and management challenges.
SambaNova’s Foundation Model Platform delivers value and innovation across the full AI stack hardware, software, systems, and even pre-trained models – to enable research organizations toachieve a 6x performance advantage over GPU based systems on the most challenging foundation
models and deep learning workloads. For research organizations, this means 6x more experiments
and 6x more discoveries with the potential to change the world.

The SambaNova Foundation Model Platform
Innovation at every layer of the stack2

SAMBANOVA DATASCALE FOR SCIENCE5123 resolution medical image analysis
High resolution 3D computer vision has the potential torevolutionize the diagnosis of serious diseases while
simultaneously accelerating and improving patient treatment
and care. 5123 resolution images both deliver a more accurate
diagnosis prediction and enable medical professionals to view
and assess a more complete picture of a patient’s health than
was previously possible.
The memory constraints inherent to GPU-based AI infrastructure
limits the resolution of 3D medical images that can be analyzed
with those systems, requiring tiling or down sampling, which
reduces resolution, increases complexity and significantly lowers
accuracy.
The SambaNova platform delivers industry leading performanceand, with 12.8x more memory than GPUs, can analyze full 5123
3D images and beyond without the need for complex tiling ordecreasing image resolution. This enables medical professionals
to make more accurate diagnosis in less time to have adramatic impact on the quality and patient care and outcomes.
The improved accuracy from higher resolution computer visionmodels reduces both missed diagnosis, as well as false positive
diagnosis, allowing medical experts to focus their time onpatients who need treatment the most.

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Large Language Models (LLMs) for Science
Large language models (LLMs) can unlock insights in
unstructured data with human level accuracy and solve dozensof language tasks with a single model. Beyond traditional
language tasks, these models have demonstrated potential inscientific domains by becoming ‘experts’ in specific topics, suchas genomic data for Covid-19 research.
Deep learning is revolutionizing research by unlocking insights
trapped in unstructured data, such as research reports, studies,scientific journals, and more. However, training custom LLMs on
domain specific scientific topics is a complex and technicallychallenging process on GPU-based systems.
SambaNova’s Dataflow architecture and large
memory enable research organizations to train custom
LLMs with a scientific corpus that can understanddomain specific content, without the massive
parallelization needed with GPU-based systems.
Delivering 6x faster performance over legacy GPU-basedsystems, researchers can take advantage of the power of theSambaNova platform to make ground breaking discoveries 6x
faster than before, while leveraging the power of LLMs to further
validate their findings before publication.

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SAMBANOVA DATASCALE FOR SCIENCE

Deep learning accelerated surrogate models
Surrogate models are deep learning models that replace one ormore components of larger multi-physics simulation workloads,
such as computational fluid dynamics or weather forecasting.
However, the GPU/CPU-based architectures used to compute
these simulation workloads struggle to deliver performance onsparse, detailed deep learning models.
Research organizations must either operate both types ofworkloads on the same architecture, or tradeoff gained speedwith added latency from shifting data between different systems
optimized for each of the different workloads.
The SambaNova platform significantly improves theperformance of sparse, detailed deep learning models
compared to GPU-based architectures, even taking
into consideration the additional latency requirementsof two different systems.
Utilizing the SambaNova platform, researchers can efficiently run
deep learning workloads for advanced scientific workloads, suchas computational fluid dynamics simulations, weather
forecasting, and physics informed neural networks

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Next steps
If you would like to learn more
about how organizations arepreparing for the future,
visit SambaNova.ai

Learn more at SambaNova.ai
linkedin.com/company/sambanova@SambaNovaAI
info@sambanova.ai

Customers turn to SambaNova to quickly deploy state-of-the-art AI capabilities to meet the demands of the AI-enabled world. Our
purpose-built enterprise-scale AI platform is the technology backbone for the next generation of AI computing. We enable
customers to unlock the valuable business insights trapped in their data. Our flagship offering, Dataflow-as-a-ServiceTM, overcomesthe limitations of legacy technology to power the large complex foundation models that enable customers to discover new services
and revenue streams, and boost operational efficiency. Headquartered in Palo Alto, California, SambaNova Systems was foundedin 2017 by industry luminaries, and hardware and software design experts from Sun/Oracle and Stanford University. Investors include
SoftBank Vision Fund 2, funds and accounts managed by BlackRock, Intel Capital, GV, Walden International, Temasek, GIC, Redline
Capital, Atlantic Bridge Ventures, Celesta, and several others.
Copyright © 2022 SambaNova Systems, Inc. All rights reserved.

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