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Space and Time Avails Blitzar on Open Source

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Written By: Michael Abadha
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    Summary:
  • Space and Time says that Blitzar's GPU acceleration technology benefits Web3 as it adequately meets the high computing demands of zk proof.

Space and Time has announced that Blitzar, the GPU acceleration technology that powers Proof of SQL, is now available in open-source.  Space and Time says the decision to make Blitzar an open-source project is meant to give the Web3 community a better and faster framework for creating zero-knowledge (ZK) proofs driven by Graphical Processing Unit (GPU) acceleration.

GPU acceleration and how Space and Time is implementing it

Space and Time is an enterprise-grade, blockchain-enabled, AI-powered multichain data platform. It is designed for use by developers working in the financial services, gaming, DeFi, or any other industry that demands trustworthy data. With the August alpha release of Proof of SQL, the company has a frontrunner in the ZK field.

Proof of SQL is a cryptocurrency designed to enable developers to integrate analytics with smart contracts. This could revolutionise blockchain technology and lead to a myriad of innovative use cases and business logic. Smart contracts can now ask verifiable questions about data from their own chain, other chains, or off-chain sources thanks to this ZK proof.

By open-sourcing the Proof of SQL GPU acceleration framework, Space and Time believes that ZK proofs will become faster, more robust, and more commonly across Web3. This, in turn, will enable a new generation of protocols, Dapps, and enterprises that are powered by verifiable computation. As their first open-source release, Blitzar marks a significant milestone for the Space and Time team.

Blitzar is the framework that allows Proof of SQL to use GPU acceleration. GPUs are the ideal hardware for the Blitzar framework because of their ability to handle intensive computational tasks, such as ZK proof generation. Next-generation ZK proofs, such as Proof of SQL, rely on GPUs because of their efficient memory structure for dealing with big datasets.

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Written By: Michael Abadha

Michael is a self-taught financial markets analyst, who specializes in analysis of equities, forex and crypto markets. He draws his inspiration from the fact that markets provide an interface through which the world interacts in search of a better tomorrow.

Published by
Written By: Michael Abadha