WHITEPAPERWriten by:Dan Desjardins

www.sparc.network

August 2017

A DISTRIBUTEDINFRASTRUCTURE-AS-A-SERVICE

PROVIDING CLOUD-BASEDHIGH-PERFORMANCE COMPUTING

TABLE OFCONTENTS

03

04 INTRODUCTION

ABSTRACT

05 MARKET CHALLENGESAND OPPORTUNITIES

06 DISTRIBUTED NETWORKARCHITECTURE AS A SOLUTION

08

09 MEET THE TEAM

CROWDFUNDING

10

11 REFERENCES

11 INDEXES

CONCLUSION

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ABSTRACT

Historically, access to high-performance computing systems has been lim-ited to large firms possessing the human, technical, and financial resources required to own and operate them. As big data morphs into bigger data, computational problems spiral upwards in complexity, and new high-tech computation-dependent fields emerge, developers are seeking new tools and methods to employ. In response to this growing demand, companies including Amazon EC2 and Google Compute Engine have recently been of-fering cloud-based computing services to small to medium-size developers requiring computational resources to attain a myriad of objectives. However, as developers and market demand migrate towards cloud-based high-per-formance computing, existing centralized architectures will quickly become outpaced. Distributed computing is the only solution to this problem of scal-ability: a global network of computers is far more powerful than any super-computer.

The unaddressed challenge with this global architecture lies in the mediation of transactions between the users who commit the projects and the compute nodes that perform the work.

SPARC is a distributed infrastructure-as-a-service that will dynamically allo-cate computational resources to user projects, using Science Power and Re-search Coins (SPARC) to quantify and remunerate completed computational work. Specifically, users requiring compute power purchase SPARC tokens from an exchange and attach them to their projects. These tokens are dis-tributed to the computational resource owners in proportion to work per-formed. SPARC tokens can then be exchanged directly for computing power from the network or traded for conventional currency on an exchange.

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INTRODUCTIONIn our era of exponential data growth, industry and academia is realizing that it must achieve a fundamental transformation in how operations are run and innovation is achieved. This transformation will require a step change in thinking and an openness that may not have been present before. The key lies in cloud adoption. Due to a convergence of multiple technologies, including ubiquitous wireless communication, real-time analytics, machine learning, and embedded systems, the commoditization of compute power resources is inevitable. Already, cloud computing has become a highly de-manded service or utility due to the advantages of high computing power, cheap cost of services, high performance, scalability, accessibility as well as availability. The International Data Corporation (IDC) forecasts that the High-Performance Computing (HPC) sector will experience a Compounded Annual Growth Rate (CAGR) of 8 percent bringing total market to USD $31.4B by 2019 [1]. Infrastructure-as-a-Service (IaaS) is projected to grow 36.8% in 2017 to reach USD $34.6B [2].

Big Data and Business Analytics (BDA)Forecasts worldwide revenues for BDA will reach $150.8 billion in 2017, an increase of 12.4% over 2016. Commercial purchases of BDA-related hardware, software, and services are expected to maintain a CAGR of 11.9% through 2020 when revenues will be more than $210 billion.

Examples of computation-intensive sectors:

Science, Technology, Engineering and Mathematics (STEM) re-searchers and industriesFor example, the market for neural network software is projected to grow from USD $7.17B in 2016 to $22.55B by 2021 [3]. Driven by uncategorized and newly digitized data, neural networks are com-putation-intensive sorting machines.

Video and Image renderingRendering and visualization software is expected to grow at a com-pounded annual growth rate (CAGR) of 30.03% from 2016 to 2020 [4]. 3D enabled display devices, virtual and augmented reality, and high-end video games are driving this growth.

Advanced Risk AnalyticsRisk analytics has a predicted CAGR of 15.3% bringing the market from USD $17.60B in 2017 to $35.92B by 2022 [5]. Emerging tech-nologies such as artificial intelligence enable institutions to improve underwriting decisions and increase revenues while reducing risk costs.

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MARKET CHALLENGES AND OPPORTUNITIES

Centralized IaaS firms, examples listed in Figure 1, are emerging in response to an upward spiraling global demand for computing power.

SPARC has identified the following opportunities and challenges in the exist-ing market:

High growth-rate of HPC requirements. A large market is available for competitive cloud-based computing services.

A vast supply of computing resources exists in the form of underuti-lized personal and commercial computer assets. These resources can be networked to form a distributed IaaS platform providing high-performance computing power to science and industry. This architecture incurs limited additional infrastructure, operation and maintenance costs.

Existing centralized IaaS providers incur higher costs to acquire, op-erate, maintain, update and expand costly infrastructure and dedi-cated hardware. Higher costs ultimately result in higher pricing; the customer pays for it.

Public Cloud Revenue %Market Share 2017

36%

10%

4% 3%

47%

Amazon Web Services, 47%

IBM Softlayer 3%

Microsoft Azure 10%

Google Cloud Platform 4%

Other 36%

Figure 1: Public cloud revenue market share 2017

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DISTRIBUTED NETWORK ARCHITECTURE AS A SOLUTION

SPARC is the first North American distributed IaaS providing consumers with affordable, flexible, and easily accessible high-performance cloud-based computing. To achieve this, we are

Leveraging existing demand and infrastructure. The Berkeley Open Infrastructure for Network Computing (BOINC) is a computing plat-form comprised of 1,128,897 compute nodes. At 17.1 petaFLOPS, it is the third most powerful supercomputer on Earth and supports computing projects in astrophysics, mathematics, and biology, for example. The alpha version of our network connects to the BO-INC network and rewards participant nodes with Science Power and Research Coins (SPARC) for computational work performed. Researchers and developers requiring computing power purchase SPARC tokens from an exchange and attach them to their projects. These tokens are distributed to the participant nodes in proportion to work performed. SPARC tokens can then be exchanged directly for computing power from the network or traded for conventional currency on an exchange.

Recapturing wasted computing power. We have identified inef-ficiencies in existing blockchain currencies. For example, in the competition-based process of hashing a digital transaction on the Bitcoin network, approximately 5,000 peta hashes per second are discarded. This amount of wasted compute power is equivalent to approximately 64,000x the combined power of the Top 500 Super-computers. Instead of hashing to determine proof-of-work, SPARC is compensating participant nodes for actual work performed. We are effectively recapturing wasted computing resources and mak-ing them available to science and industry.

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Varying hardware allocation instead of varying pricing. Whereas Ama-zon EC2, Google Cloud Compute and other services vary the price as a function of system loads, our network varies the hardware dedicated to your service via an auction process. We allow you to set your price point and let the network compete for available jobs. This ensures 100% network usage, and potentially high rates of power at low cost without added setup for your project.

Expanding infrastructure by connecting new compute assets to our cloud. Compute resource consumers can also participate as suppliers earning SPARC tokens that can be used to fund their own usage, or be traded for conventional currency on an exchange. This is an example of demand creating supply. SPARC foresees that imminently arriving self-driving automated vehicles, each containing Massively Parallel Pro-cessing (MPP) units, when not in operation, will network together form-ing one of the most powerful distributed supercomputers on Earth. The Internet of Things allows for any device to participate in our distributed computing network, earning SPARC for device owners and providing compute power for users.

Low costs relating to infrastructure, operations, and maintenance trans-late directly into more affordable services for our users.

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CROWDSALE

Our second round is designed to open our network up to the broader public.

Once the Alpha release has started gaining traction we will be turning our attention towards the proprietary network. This network will allow us to open up to commercialization and streamline delivery of content.

We will be raising funds for progressing development towards release. Q1 2018 is our projected release for the minimum viable product. This release is targeted at bringing new users and agile projects onto the system. Moving forward we will be expanding support to niche cases and developing exten-sions for proprietary programs such as MatLab and COMSOL.

Our goal is to establish a long term budget to ensure continuation of the network. This will give miners and projects confidence moving onto our plat-form.

The minimum cap is set to ensure we have critical mass to launch our net-work. If we should fail to meet the minimum cap, we will be continuing to build support on our Alpha, and developing our network while aiming for a successful funding round in the future.

Please do not send your purchase from an exchange address. If you do, your tokens can be recovered, but this is a manual process and may take several days involving proving your ownership of that address.

Tentative Start Date

End Date

Minimum Cap

Maximum Cap

Exchange Rate

Round 1 Participant Bonus

Bounty Tokens

Developer Equity

Crowdsale Contract Address

Token Contract Address

October 1st 2017

30 Days after start

250,000,000 SPARC

2,500,000,000 SPARC

1 ETH : 10000 SPARC

Additional 100% to max ofRound 1 Participation

1% of Tokens Sold

5% of Tokens Sold

To Be Released

Etherscan

Round 2

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DOUGLAS STEWARTFOUNDER, CEO

A serial entrepreneur this will be Doug’s third online company. His first success-fully acquired, the second, Quetzal a leader in cloud based point-of-sale, is still growing. Doug is a team builder and with 20 years of management he brings val-uable experience and con-nections to the company.

GREG AGNEWFOUNDER, CTO,LEAD DEVELOPER

Greg was a also founding member of the Quetzal four. Always at the fore-front of technology, he has mastered Ethereum and full stack development. Spending his spare time building chess engine style games in web applications he is an expert in pushing V8 to the limits.

DANIEL DESJARDINS, PHDVP OF BUSINESSDEVELOPMENT

A serial entrepreneur this will be Doug’s third online company. His first success-fully acquired, the second, Quetzal a leader in cloud based point-of-sale, is still growing. Doug is a team builder and with 20 years of management he brings val-uable experience and con-nections to the company.

EDDIE ROOSENMAALLENSYSTEMS ARCHITECT

Eddie is a full-stack engi-neer with over a decade of experience in rich web apps on both physical and cloud deployments. He is a veter-an teammate of ours, hav-ing worked together at both DAS and Vivonet.

ANNE VIVIAN-SCOTT, MBA, PENGCOMMERCIAL ADVISOR

President and CEO BKIN Technologies“The majority of my career has been occupied by the challenging task of commer-cializing university-based research discoveries into meaningful products and services. The KDS initiative is a timely innovation that will have the full support of researchers requiring dis-tributed supercomputing power.”

MACK VAN ROSSEMRESEARCH ADVISOR

Former South Pole data center operator for the IceCube Neutrino Obser-vatory Mack has worked slicing data and sending it over networks for use back home. He has a passion for reducing wasted computa-tional power and improving our efficiency with this criti-cal resource.

MEET THE TEAM

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CONCLUSION

SPARC offers a truly disruptive solution to growing global demand for cloud- based, high-performance computing. Compared to centralized IaaS platforms, our network delivers cost-effective, flexible, and powerful computing power. The SPARC network can endlessly expand its infrastruc-ture by connecting underutilized computer assets to the network, and re-captures wasted computing power from proof-of-hash blockchains. Our distributed architecture is sustainable and eco- friendly, promoting full usage of existing hardware instead of commissioning and operating new infrastructure. SPARC envisions a world in which anyone with a laptop and an internet connection will have the power of a supercomputer at their fingertips.

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Feldman,M.(2016,Nov30).IDC’sLatestForecastfortheHPCMarket:“2016 is Looking Good” [Article]. Retrieved from https://www.top500.org/news/idcs- latest-forecast-for-the-hpc-market-2016-is-looking-good/

APPENDIXReferences

Pettey C. and Goasduff L. (2017, Feb 22). Gartner Says Worldwide Public Cloud Services Market to Grow 18 Percent in 2017 [Press release]. Retrieved from http://www.gartner.com/newsroom/id/3616417

CISIONPRNewswire.(2017,Jan23).NeuralNetworkSoftwareMarketbyType, Vertical, and Region - Global Forecast to 2021 [Article]. Retrieved from http:// www.prnewswire.com/news-releases/neural-network-software-market-by-type- vertical-and-region---global-forecast-to-2021-300395057.html

Business Wire. (2016, Mar 31). Visualization and 3D Rendering Software Market 2016-2020 - High-End Video Games, Architectural and Product Vis-ualization, TrainingSimulation,MarketingandAdvertisement-Research-andMarkets[Article]. Retrieved from http://www.businesswire.com/news/home/20160331005465/en/ Visualization-3D-Rendering-Software-Mar-ket-2016-2020--

Markets and markets. (2017). Risk Analytics Market worth 35.92 Billion USD by 2022 [Article]. Retrieved from http://www.marketsandmarkets.com/ PressRe-leases/risk-analytics.asp

INDEXSPARC Science Power and Research Coin

CAGR Compounded Annual Growth Rate

HPC High Performance Computing

IDC International Data Corporation

IaaS Infrastructure-as-a-service

BDA Business Data Analytics

BOINC Berkeley Open Infrastructure for Network ComputingSTEM Science, Technology, Engineering and MathematicsFLOPS Floating point operations per second

MPP Massively Parallel Processing

[1]

[2]

[3]

[4]

[5]

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