Hypernet is a protocol for parallel computing over a decentralized, dynamic, distributed network utilising idle computational power. It provides an API suite to efficiently perform global data operations in parallel that are robust to limited bandwidth and peer dropout using Distributed Average Consensus (DAC) over a decentralised network of devices.

Rating: 4.0

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Details Description Risks Full analysis Team

Detailed review

Stage of product development
Blockchain Scheduler and Consensus API should be developed in August 2018. The last part of the whole product is Runtime Environment, which should be developed in December 2018.

Token description
ICO date
Token price
Token distribution date
Consensus method
ICO currencies
Bounty camping
Token functions
Tokens would perform four interconnected and critical functions: 1) Collateral  2) Network Allocation 3) Reputation 4)Priority of tasking

Economy of scale and almost unlimited access to capital could make centralized models extremely efficient and cheap.


DAC has not been explained properly in white paper.


Hard cap and total market caps is not announced yet.

Full analysis

Hypernet is going to work on huge and fast-growing market. According to Gartner, market of Cloud System Infrastructure Services (IaaS) has revenue $40.8 bln in 2018 and is expected to be more than $80 bln in 2021. Currently, this market is dominated by huge players such as Microsoft and Amazon. However, Hypernet and other same project could acquire huge market share on this markets. Even 1% on such market would be $800 mln yearly in 2021. Main competitors of Hypernet (Golem, Sonm, and iExec) currently focused on solving very specific issues. Golem is currently heavily focused on rendering. Sonm is primarily adapting existing hub and spoke architectures, with an emphasis on server hosting, to distributed networks. iExec is focused on decentralized cloud computing, for specific use in certain research applications. Hypernet is going to develop more widely used solution.


The product of Hypernet is based on years of research and work of founders. It consist of two sides of product – on-chain task scheduler and off-chain technologies. They has developed a new parallel programming model, what they call Distributed Average Consensus (DAC). This allows for data reductions to be performed for massively parallel problem sets. DAC, which powers the Hypernet, takes a new approach that has been built from the ground up to specifically perform distributed computing. DAC+Blockchain allows for the efficient distribution of compute jobs, and effectively manages computers dropping on and off the network. The DAC algorithm is efficient, scalable, robust, and allows for the most complex computations that exist today to be conducted in a decentralized fashion, and enables new forms of computation that cannot optimally be done in a centralized fashion. Both the on-chain (scheduled) and off-chain (DAC) technology layers of Hypernet fit together hand in glove, and are both driven by consensus. In contrast, Golem, Sonm, and iExec have built their technical foundations on traditional computing architectures. These architectures were originally developed specifically to be used in data centers, and each group has bolted this data center architecture onto a blockchain network. This is perhaps why Golem, Sonm, and iExec seem to currently be focused on solving very specific issues.

Business model

Hypernet tokens would not be just currency within the platform. It performs four interconnected and critical functions that enable a marketplace for decentralized computational power over dispersed, dynamic networks: 1. Collateral — Buyers and sellers of computational power will use tokens as a form of collateral for launching and fulfilling compute jobs. This will ensure fairness for all parties and limit misuse of Hypernet by bad actors 2. Network Allocation — Hypertokens will be used to allocate and measure capacity for submitting and running compute jobs. 3. Reputation — Hypertokens will allow ecosystem actors to build a verifiable reputation and increase their standing in requesting and fulfilling compute jobs. 4. Priority — The prioritization of jobs will be moderated within Hypernet via the previous three factors of reputation, network allocation, and collateral. As a result, we believe, that HyperTokens creates additional value on the platform. Also, it is clear that the value of tokens would rise with the growth of platform usage.


Financial details of the project has not been announced yet. However, we could track the competitors and make some estimations, based on market size. Projects in same field, which already came to exchanges: Golem (Mrk Cap – $523 mln), iExec RLC (Mrk Cap – $132 mln), SONM (Mrk Cap – $75 mln), GridCoin (Mrk Cap – $16 mln). As was mentioned before, even 1% on cloud computing market means nearly $800 mln revenue. Tokens would be extremely important part of whole ecosystem. There would be 100 mln tokens issued. As a result, each token would constitute $8 of revenue. If we assume, that each token would circulate 10 times a year, the minimum price for 1 token would be $0,8, as a result, it would mean total capitalization of the company equal to $80 mln.


The project has very strong team with huge blockchain experience. One of the founder, Daniel Maren, was a member of the Stanford Bitcoin Mafia. One of the earliest adopters of Bitcoin in 2013. Daniel studied computer science at Stanford University. He founded a solar power electronics company, Dragonfly Systems, which was acquired by SunPower Corporation in 2014. In addition, he is a Forbes 30 under 30 award recipient. Other co-founder, Ivan Ravlich, got his masters in aeronautics and astronautics at Stanford. Ivan has worked for several startups, for example AdAstra, a plasma rocket startup and LanzaTech, a alternative fuel startup. His PhD research at Stanford focused on advanced space propulsion from magnetoplasma rockets to extended theories of gravity. The last co-founder is Todd Chapman. He also PhD in Stanford. He was awarded a Department of Defense National Defense Science and Engineering Graduate fellowship in Stanford’s Aeronautics and Astronautics department. Todd’s current research interests are in fault-tolerant algorithms for distributed and exascale computing and applying optimal control methods for training stabilized neural network architectures. Lead Engineer of the project, Christopher Hansen, has extremely strong background in technologies. He studied electrical engineering and computer science at Stanford University. During his study, he had internship at Facebook and Twitter. Moreover, he concurrently completed Masters with Bachelors degree. Christopher worked on the cutting edge of the infrastructure that powers machine learning and HPC. After completing his Master’s degree, he joined NVIDIA to work on their next generation GPU technology. The project also has incredible advisory board. Randall Kaplan is a co-founder of Akamai Technologies, the global leader in Content Delivery Network (CDN) services. (nearly 25% of the world’s web traffic). Joseph Urgo is the co-founder of District0x, an Ethereum dApp decentralizing the world’s marketplaces. Prior to this, Joseph founded Sourcerers.io, a consultancy supporting leading Ethereum-based projects. Tony Reeves is the Chief Financial Officer of Global Technology for Experian plc. (It has revenue of $4.6B, with a presence in 37 countries) As a result, we truly believe, that such amazing team could cope with this extremely hard target to build solution for distributed computing.

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