HOW
HOW
HOW
DYNEX WORKS
DYNEX WORKS
DYNEX WORKS

Run a
Compute Job

Computing tasks are published to the Dynex platform conveniently through Python using the Dynex SDK.

01

Define the computing task in Python

02

Buy & deposit DNX (FIAT based)

03

Define block fee / solution reward and run the computation

Dynex Mallob Activates

Miners aid in solving tasks by mining DNX. Dynex Mallob, a system that organizes and prioritizes the jobs submitted by Dynex clients, begins operating.

01

Setting number of chips to be utilized

02

Markov-chain based parameter tuning

03

Computational data exchange runs for tasks

04

Solution & computation verification (PoUW)

Miners’ Job Reward

Upon finalisation of a computational task (job), DynexSolve miners receive a significant amount of DNX as block reward.

01

Miners receive DNX for the task completion

02

Rewards distributed once block fees are calculated

Supported Tasks

machine learning

Quantum-Support-Vector-Machines (QSVM), Quantum-Boltzmann-Machines (QBM) and others

deep learning

Quantum Neural Networks (QNN), Quantum K-Means Clustering and QBoost classifiers.

FEDERATED ML

Federated machine learning, feature selection and training tasks

Ising/QUBO

Quadratic unconstraint binary optimisation problems and Ising sampling (QM, BQM, CQM, QUBO)

sat

Boolean satisfiability problems

maxsat

Maximum satisfiability problems

SUBSET SUM

Subset Sum problems

MILP

Mixed Integer Linear problems

Frequently Asked Questions

Frequently Asked Questions

Frequently Asked Questions

And The answers

And The answers

And The answers

What is Dynex?

Dynex is a next-generation platform for neuromorphic computing based on a new flexible blockchain protocol. It consists of participating nodes that together constitute one enormous neuromorphic computing network.

Consequently, the platform is capable of performing computations at unprecedented speeds and efficiency – even exceeding quantum computing. Everyone is welcome to participate, since the Dynex neuromorphic computing chip is capable of being simulated efficiently on graphic processing units (GPUs). Users exchange computation time for Dynex’s native token DNX, thus enabling everyone to earn money on the platform.

When/how was Dynex launched?

Dynex was built to be a battle-ready network that supports permissionless, composable tokens and provides a secure, efficient, next-generation neuromorhpic computing platform. The initial design started in 2020, with the mainnet launching on September 16th, 2022.

There is a maximum supply of 100,000,000 DNX. There was no private sales, pre-mine, or initial coin offering.

The Dynex project is community-driven and entirely focused on promoting development and widespread adoption of the Dynex platform.

How can I get DNX?

There are three possibilities to obtain DNX, Dynex’s native token:

  • Perform mining (proof-of-work) on your computer systems and get rewarded – on CPU, GPU and FPGA

  • Run the Dynex Neuromorphic Chip on your computer systems and get paid for the usage on a per minute basis – on CPU, GPU and FPGA

  • Buy DNX on an exchange

Learn More →

Is Dynex green?

In light of the growing threat of climate change to our environment and our future, it is imperative that we take every measure necessary to reduce global energy consumption. An accelerated adoption of neuromorphic computing will therefore benefit our entire society since it uses orders of magnitude less energy compared to traditional computing systems. For more information, read our publication “Smart Mining — Reinventing the Cryptographic Puzzle to Make it More Meaningful

What is the Dynex emission schedule?

There’s no initial coin offering („ICO“), no pre-mining and no coin drop for developers or any other hidden incentive built into the token.

Upon launch of the
Dynex mainnet, all 110,000,000.0 DNX tokens will be available according to the emission schedule. To ensure the smoothness of the emission process we use the following formula for block rewards: BaseReward = (MSupply − A) ≫ 18, where A is amount of previously generated coins. A new block is generated every 120 seconds in the Dynex blockchain.

Dynex mainnet launched on September 16th, 2022.

What is the maximum supply of Dynex tokens?

There is a maximum supply of 100,000,000 DNX.

Is there a wallet for Dynex?

First, there’s the Dynex Mobile Web Wallet. No installation, no download, just two clicks to get started.

There is also a convenient Dynex wallet app for Windows, MacOS and Linux. You can download and install it from our GitHub repository. Here’s how it looks:

How can I run a Dynex node?

Users who are contributing CPU resources are getting compensated on a “per computing step” basis. As you are running a Neuromorphic Chip on your regular machine, the Dynex chip will be simulated on it (by numerically integrating the equations of motion of the circuit, but that’s more a tech detail, see below). We measure the speed of the integration in “Integration Steps”, which is also the basis for your compensation. You can choose how much you charge per 1,000 integration steps, which is then matched with the computing requests and what their budget is. As a rule of thumb, 1,000 integration steps require around 1 minute of real time on a Macbook Pro per core. You can run multiple cores with the command “start_dynexchip <NUMBER OF THREADS>”:

To stop your Dynex chips, use the command “stop_dynexchip”. You will be compensated every 1,000 integration steps with DNX which you will receive in the wallet you have specified (or from where you have started the chips). Every 1,000 steps your node submits your proof-of-work of your computations to the customer, who in turn can quickly verify the correctness of the calculation.

RUN YOUR NEUROMORPHIC CHIP

How much do I earn when I run a Dynex Chip on my machine?

Users who are contributing CPU resources are getting compensated on a “per computing step” basis. As you are running a Neuromorphic Chip on your regular machine, the Dynex chip will be simulated on it (by numerically integrating the equations of motion of the circuit, but that’s more a tech detail, see below). We measure the speed of the integration in “Integration Steps”, which is also the basis for your compensation. You can choose how much you charge per 1,000 integration steps, which is then matched with the computing requests and what their budget is. As a rule of thumb, 1,000 integration steps require around 1 minute of real time on a Macbook Pro per core. You can run multiple cores with the command “start_dynexchip <NUMBER OF THREADS>”:

To stop your Dynex chips, use the command “stop_dynexchip”. You will be compensated every 1,000 integration steps with DNX which you will receive in the wallet you have specified (or from where you have started the chips). Every 1,000 steps your node submits your proof-of-work of your computations to the customer, who in turn can quickly verify the correctness of the calculation.

How do I mine Dynex?

Dynex mining is based on a memory-hard algorithm which is designed to be Proof of Work algorithm. It can run on CPUs and on most low-end GPUs at cooler temperatures than other algorithms – increasing mining equipment longevity.

Start Mining →

Why Proof-of-Work?

Dynex mining is based on a memory-hard algorithm which is designed to be Proof of Work algorithm. Instead of searching for hashes to secure the blockchain, Dynex mining also performs useful computations, for example for Machine Learning, AI, medical research, optimization problems and more.

Start Mining →

Why neuromorphic computing?

Neuromorphic computers offer a number of fundamental operational advantages:

  • Inherently parallel operation is a characteristic of neuromorphic computers, where all neurons and synapses can potentially operate simultaneously; however, when compared with the parallelized von Neumann systems, neurons and synapses perform relatively simple computations.

  • Memory and processing are co-located: in neuromorphic hardware, there is no concept of separating memory and processing. In many implementations, neurons and synapses perform processing and store values in tandem, despite the fact that neurons are sometimes thought of as processing units and synapses as memory units. By combining the processor and memory, the von Neumann bottleneck regarding processor/memory separation is mitigated, resulting in a reduction in maximum throughput. Furthermore, this collocation reduces the need for data access from the main memory, which consumes a large amount of energy compared to compute energy.

  • Neuromorphic computers have inherent scalability since adding more neuromorphic chips increases the number of neurons and synapses. . In order to run larger and larger networks, it is possible to treat multiple physical neuromorphic chips as a single large neuromorphic implementation. Several large-scale neuromorphic hardware systems have been successfully implemented, including SpiNNaker and Loihi.

  • Neuromorphic computers use event-driven computation (meaning, computing only when available data is available) and temporally sparse activity to achieve extremely high computational efficiency. There is no work being performed by neurons and synapses unless there are spikes to be processed, and typically spikes are relatively sparse in the network operation.

  • Stochasticity can be incorporated into neuromorphic computers, for instance when neurons fire, to accommodate noise.


Can I run the Dynex Neuromorphic Chip on my Laptop?

Dynex can be mined on laptops which have a GPU.

Can Dynex scale?

Due to its nature as a platform, Dynex is expected to support long-term contracts for at least the lifetime of an average person. Dynex focuses on using stable, well-tested solutions. Many of the solutions used in Dynex have been formalized in papers that have been presented at peer-reviewed conferences and have been widely discussed in the community.

The Dynex Platform leverages this dynamics to accelerate and enable new methods for solving discrete optimization, sampling, and machine learning problems. Dynex uses a process called neuromorphic annealing to search for solutions to a problem. Neuromorphic annealing is fundamentally different from classical computing.

Copyright © 2024 Dynex. All rights reserved.

Copyright © 2024 Dynex. All rights reserved.

Copyright © 2024 Dynex. All rights reserved.