Bitcoin:Next
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What are the next changes that we might see in the near future coming to Bitcoin? Improvement in the signature algorithms and scripts leading to better privacy and size optimizations
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"The Kokkos C++ Performance Portability EcoSystem is a production-level solution for writing modern C++ applications in a hardware-agnostic way. The ecosystem is part of the U.S. Department of Energy's Exascale Project, a national effort to prepare the HPC community for the next generation of supercomputing platforms. We'll give an overview of what the Kokkos EcoSystem provides, including its programming model, math kernels library, tools, and training resources. We'll provide success stories for Kokkos adoption in large production applications on the leading supercomputing platforms in the U.S. We'll focus particularly on early results from two of the world's most powerful supercomputers, Summit and Sierra, both powered by NVIDIA Tesla V100 GPUs. We will also describe how the Kokkos EcoSystem anticipates the next generation of architectures and share early experiences of using NVSHMEM incorporated into Kokkos."
Watch the video: https://wp.me/p3RLHQ-kjh
Learn more: https://github.com/kokkos
and
https://www.nvidia.com/en-us/gtc/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Types - slice, map, new, make, struct - Gopherlabs
This document provides an overview of Go programming concepts including slices, maps, structs, make, and new. It includes links to interactive code examples demonstrating how to use slices to store and access elements, maps to associate keys with values, and structs to group related data. The key differences between make and new are explained, where make is used to initialize slices, maps, and channels, and new returns a pointer to a newly allocated zero value.
COSCUP2023 RSA256 Verilator.pdf
In this slide, I introduce how I implement RSA256 algorithm with verilog and verify with verilator.
The project use C++ to build the C-model and SystemC model.
To help build the model, we create a C++ class vint to simulate the behavior of Verilog. It supports normal Verilog operation with more strict rules.
The systemC model can be directly translated into Verilog, so the intention of Verilog design is quite clear and concise.
To simplify the simulation, we limit our module to be one input port and one output port. The port uses the valid/ready protocol to control the data flow, which can be modeled as sc_fifo in systemC.
With these abstraction, we can easily implement unit test for all of our modules, and make sure they act as what we want.
----
Please access the source code at:
https://github.com/yodalee/rsa256
MySQL/MariaDB Parallel Replication: inventory, use-case and limitations
- The document discusses various parallel replication technologies in MySQL/MariaDB including schema-based parallel replication in MySQL 5.6, group commit-based approaches in MariaDB 10.0 and MySQL 5.7, and optimistic parallel replication in MariaDB 10.1.
- It provides an overview of how each approach tags and dispatches transactions to worker threads on slaves and their limitations regarding transaction ordering and gaps.
- Examples from Booking.com show how parallel replication can scale to thousands of servers but also hit issues like long transactions blocking progress.
PostgreSQL as seen by Rubyists (Kaigi on Rails 2022)
PostgreSQL has become the most popular RDBMS in the Ruby ecosystem in the last decade. It has a great set of built-in features, including a variety of versatile data types, both common and very specific.
But when we load data from the database to our application code, we're working with Ruby data types: classes from the standard library, Rails, or other gems. So while they can seem to be the same as their PostgreSQL counterparts, they are not absolutely identical, and sometimes that could lead to surprising behavior.
In this talk, I would like to explore the power of data types in PostgreSQL and Ruby and how to work with them properly to use both Ruby and PostgreSQL on 100% of their power!
MySQL Parallel Replication by Booking.com
Since 5.7.2, MySQL implements parallel replication in the same schema, also known as LOGICAL_CLOCK (DATABASE based parallel replication is also implemented in 5.6 but this is not covered in this talk). In early 5.7 versions, parallel replication was based on group commit (like MariaDB) and 5.7.6 changed that to intervals.
Intervals are more complicated but they are also more powerful. In this talk, I will explain in detail how they work and why intervals are better than group commit. I will also cover how to optimize parallel replication in MySQL 5.7 and what improvements are coming in MySQL 8.0.
Stevens 3rd Annual Conference Hfc2011
This document describes designing a customized hash function for processing market data in high-frequency trading systems. It discusses sources of latency, software and hardware optimization techniques, and implementing a data structure using a hash table with symbols as keys. The implementation initializes the hash table by loading symbols in descending order of expected activity and resolving collisions. It also describes expanding the table to add new symbols and finding an optimal hash table size to minimize collisions and costs.
H2O Design and Infrastructure with Matt Dowle
This document provides an overview of H2O, an open source machine learning platform that allows for distributed, in-memory analytics of large datasets. It discusses how H2O works, including how it uses a map-reduce style to parallelize machine learning algorithms across multiple nodes. The document demonstrates starting an 8-node H2O cluster on Amazon EC2 and importing a 23GB dataset in under a minute, significantly faster than with other tools. It also summarizes how H2O's distributed fork-join framework executes tasks across nodes and shares data through its distributed data structures.
Blockchain Cryptography for Developers (Nakov @ BGWebSummit 2018)
Elliptic Curve Cryptography (ECC)
ECC Concepts, Elliptic Curves, the secp256k1 Curve
Private Key -> Public Key -> Blockchain Address
Sign / Verify Transactions in Ethereum
Cryptographic Hash Functions: SHA256, SHA3, RIPEMD160, …
HMAC and Key Derivation: HMAC, PBKDF2, SCrypt
Blockchain Cryptography and Wallets: JSON / UTC, BIP39, BIP44
Wallet Encryption: AES + Padding + CBC/CTR, SCrypt, HMAC
from Binary to Binary: How Qemu Works
This document discusses how Qemu works to translate guest binaries to run on the host machine. It first generates an intermediate representation called TCG-IR from the guest binary code. It then translates the TCG-IR into native host machine code. To achieve high performance, it chains translated blocks together by patching jump targets. Key techniques include just-in-time compilation, translation block finding, block chaining, and helper functions to emulate unsupported guest instructions.
“Technical Intro to Blockhain” by Yurijs Pimenovs from Paybis at CryptoCurren...
He will give an introduction talk about Blockchain technology technical aspects like cryptography, protocols, APIs and scripting with focus on explaining how Bitcoin and other blockchain works and what they consist of.
Yurijs is a Chief Technical Officer at Paybis, blogger at coinside.ru , blockchain enthusiast since 2011.
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An Open Discussion of RISC-V BitManip, trends, and comparisons _ Claire
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Crossing Abstraction Barriers When Debugging In Dynamic Languages
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Types - slice, map, new, make, struct - Gopherlabs
Types - slice, map, new, make, struct - Gopherlabs
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More from Felix Crisan
Big data uservices
This document discusses trends in computing and data architectures. It notes that hardware is becoming more virtualized through containers and functions, bringing code closer to storage. Meanwhile, data structures are becoming more distributed through databases, distributed databases, and distributed ledgers. Computing scopes are decreasing while storage scopes are increasing. This is because data is inert but code can be more tightly controlled at smaller scopes. The document also discusses challenges of integrating microservices with data, including consistency, and notes the importance of people and processes ("metadata") alongside technology.
BigData in BlockChains
Blockchains provide a fertile ground for storing and managing big data in a decentralized manner. Some examples of using blockchains for big data include Numer.ai for storing machine learning data shapes, IPFS and FileCoin for distributed storage, and BigchainDB as a distributed database with blockchain characteristics. Blockchains allow users to store and control their own data while granting view rights to interested and trusted parties, making it even GDPR compliant by keeping users as the data controllers.
Lightning Network
The document discusses the Lightning Network, which aims to scale bitcoin transactions by enabling instant, low-cost payments through off-chain payment channels. It describes key concepts like payment channels, routing payments across multiple nodes, and implementations. The Lightning Network allows for near-instant micropayments, smart contracts, and cross-chain atomic swaps by using timelocks and hashed timelock contracts to securely transfer bitcoin off the main blockchain.
Smart contracts using web3.js
Smart contracts can be deployed and executed on the Ethereum blockchain using web3.js. Web3.js is a JavaScript API that allows interaction with Ethereum clients like Geth to deploy contracts, call contract functions, and get information from the blockchain. Contracts are written in languages like Solidity and deployed through transactions that store the compiled code at an address. Once deployed, the contract code and data resides on the blockchain and can be interacted with through web3.js by calling functions or accessing public variables.
Smart contracts in Solidity
Smart contracts are computer protocols that facilitate, verify, or enforce the negotiation or performance of a contract. On Ethereum, a smart contract is code and data that resides at a specific address on the blockchain. The Ethereum Virtual Machine is the runtime for smart contracts, which can call other contracts, have storage to store data, and can remove themselves from the blockchain. Smart contracts are defined through transactions and deployed to the blockchain, then users can interact with them through their ABI interface. Developers use languages like Solidity to code smart contracts and tools like Truffle to test contracts locally before deployment.
Mashing the data
A proposal for replicating relational databases to non-relational ones. We choose Google Cloud Datastore, but could as well use MongoDB
Big(data) in block(chains)
This document provides an overview of Bitcoin and blockchain technology. It describes how Bitcoin was created in 2008, functioning as a transmission protocol, distributed ledger, and stored value account without the need for settlement. Transactions are recorded on a blockchain, with a new block added every 10 minutes. The blockchain records transaction hashes in blocks linked by cryptographic hashes. Analyzing Bitcoin transaction data can provide useful statistics about usage trends, price movements, and detect spam attacks.
Enablers for o commerce
oCommerce is omniCommerce. If we talk about omni channel why do we keep talking about mCommerce and eCommerce?
mcommad
MCOMMAD discusses blending advertising and mobile commerce (m-commerce). It provides an overview of NETOPIA, the largest SMS aggregator and payment gateway in Romania, and their mobilPay mobile wallet. The document notes that while mobile advertising currently makes up around 5% of global ad spend, mobile purchases account for 35-40% of all purchases. It introduces the mobilPay wallet as not just a payment tool but a marketing platform, allowing clear tracking of transactions resulting from marketing actions. Features mentioned include Push2Pay notifications, offline in-store functionality, and QR/BLE/NFC codes to enable online and offline interactions.
NoSQL solutions
MongoDB and Redis are popular NoSQL alternatives to SQL databases. MongoDB is a document-oriented database that does not require a predefined schema and allows embedding documents. It supports features like sharding, replication, and indexing. Redis is an in-memory key-value store that persists data to disk. It supports data structures like strings, hashes, lists and sets. Both databases are commonly used for caching, queues, and other use cases where flexibility and performance are important.
Deconstructing Lambda architectures
The document discusses the lambda architecture, which is designed to handle large volumes of data and queries over that data. It describes the three main layers - batch, speed, and serving layers - that make up the lambda architecture. The batch layer handles batch processing and generates a master dataset. The speed layer handles real-time queries and compensates for latency in the batch layer. The serving layer indexes and exposes views of the data to support ad-hoc queries.
402 @ Mobile next
This document discusses the history and current state of Bitcoin and blockchain technology. It provides an overview of Bitcoin's origins with Satoshi Nakamoto's 2008 whitepaper, the genesis block from 2009 referencing the financial crisis, and prior related work. Benefits of Bitcoin include anonymity, transparency, security, and speed of value transfer. Use cases mentioned include escrow, smart contracts, issuing securities, and digital notaries. Challenges integrating with traditional finance are noted. The document concludes with background on the author's payments company in Romania.
Presentation for the first Bucharest Big data meetup
RT Analytics provides real-time analytics and insights for their mobile payment and SMS aggregation businesses in Romania. They use a data streaming platform with Storm for scalable stream processing, RabbitMQ for queuing transaction data, and Redis for fast in-memory storage. This allows them to aggregate transaction details in real-time by merchant, status, error, currency and time interval. The setup provides operational insights, transaction monitoring, and business dashboards to gain better understanding of queries, insights, and predictions to improve their services.
Data analysis with Pandas and Spark
This document discusses using Jupyter notebooks, Pandas, and Spark for analytics pipelines on both small and large datasets. It summarizes the challenges of working with different data volumes and timeframes. For small mobile transaction data, notebooks with Pandas and R are used, while larger retail data is analyzed with Spark ML and scikit-learn in notebooks running in Docker containers. Future work includes applying Spark to additional domains and building forecasting and streaming capabilities.
TCP/IP of money
This document discusses the history and potential of blockchain technology. It traces the origins of TCP/IP and Bitcoin, comparing Bitcoin to TCP/IP for the internet. Blockchain is described as a transmission protocol, distributed ledger, and stored value account. The document outlines increasing corporate investment and experimentation in blockchain applications across banking, exchanges, infrastructure, and other areas. It argues that blockchain will fundamentally change the financial industry in the same way TCP/IP transformed communication, and that "blockchain is the TCP/IP of money."
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My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Generative AI Deep Dive: Advancing from Proof of Concept to Production
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
National Security Agency - NSA mobile device best practices
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
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TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
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Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
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Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
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Mental Health: Maintaining balance and not feeling pressured by user demands.
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Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
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UiPath Test Automation using UiPath Test Suite series, part 6
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Test Automation with generative AI and Open AI.
UiPath integration with generative AI
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GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neha Bajwa, Vice President of Product Marketing, Neo4j
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Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
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Bob Boule
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Gopinath Rebala
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#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
Bitcoin:Next
- 1. What’s next for Bitcoin?
- 2. Topics ● Schnorr ● MAST ● Taproot ● Graftroot
- 3. Elliptic curves refresher (or intro, as the case might be) ● It all starts with a prime number, e.g. p=2256 - 232 - 29 - 28 - 27 - 26 - 24 - 1 ● And a regular looking equation, such as y2 = x3 + 7 ● And a point G (x,y - calculated from x=79BE667EF9DCBBAC55A06295CE870B07029BFCDB2DCE28D959F2815B16F81798) ● ECDSA sig (r,s) => s = r-1 (H(m)+ka)
- 4. Operations ● P=kG ● One can add points on the curve P+R=Q ● One can multiply points with scalars R=xP (can be seen as R=P+P+....+P - x times) ● Most important: aG+bG=(a+b)G (translates to: sum of pubkeys has priv key the sum of privkeys)
- 6. Schnorr signature Img Src https://medium.com/cryptoadvance/how-schnorr-signatures-may-improve-bitcoin-91655bcb4744
- 7. Warning! ● The previous graphs are valid for real numbers and we’re actually working in Zp which results in a graph that looks more like a scatterplot
- 8. Real numbers vs prime field Img Src https://www.maximintegrated.com/en/app-notes/index.mvp/id/5767
- 9. Schnorr ● Signature (k priv key P=kG, m message to sign, r - random, R=rG) s = r - h(m||R)k then signature for m is (r,s) ● Verification sG = rG - h(m||R)k => S = R - h(m||R)P
- 10. Aggregation ● The immediate benefit of Schnorr sig is that they can be aggregated and batch verified => reduction in tx size + faster transaction (maybe even block) validation time ● BIP-SCHNORR (no official # yet)
- 11. Other advantages ● Provable secure in ECDLP random-oracle model (ECDSA is _not proven_) ● Non-Maleable (in ECDSA 3rd party can alter sig for P and m into another sig for P and m) ● O(1) - due to aggregation ● Batch verification
- 12. Scripts ● Any script can be represented as a tree ○ To be more specific: even as a binary tree ○ We’re talking about stack-based Bitcoin-like scripts ○ Polish notation anyone? ● This means that one can make a commitment to a script by Merkle-izing it
- 15. MAST ● Scripts can be anyway revealed only on spend (BIP 16) ● Benefit: one does not have to reveal anything than the executed path ● Saves space ● More Privacy! ● BIP 114,117
- 16. Bitcoin Scripts - P2PKH ● “Standard signature”: OP_DUP OP_HASH160 <pkh> OP_EQUALVERIFY OP_CHECKSIG ● Same thing in “SegWit lingo” OP_0 <pkh>
- 17. Bitcoin Scripts - P2SH ● P2SH OP_HASH160 <scripthash> OP_EQUAL ● In SegWit lingo (P2WSH) OP_0 <scripthash> ● The data length classifies vs previous case (20 bytes here vs 32 before)
- 18. Taproot ● P2SH and P2PKH are distinguishable ● Can we merge both? ○ E.g. ContractHash = P + h(z||P)G ● Once we do this ○ Spending means just signing with k+h(z||P) <- works even now OR ○ Provide script z and let the stack decide <- needs a new opcode
- 19. Putting it together ● New opcode (OP_NEW) ● In output OP_NEW <pubkey> ● In input (to spend) ○ Provide <signature> in P2PKH mode ○ OR ○ <P> <script>[]<arguments> (taproot) ○ <scriptsig> <script> []<arguments> (graftroot) ● BIP-TAPROOT (no official # yet)
- 20. Graftroot ● Extension of Taproot ● Focuses on the “everybody agrees” case ● Allows delegating signing to a separate script ● Is interactive (compared to Taproot which is not)
- 21. ELTOO ● SIGHASH_NOINPUT (BIP 118) ● HF only for SegWit scripts with ver>=1 ● Allows an input _not_ to reference a specific previous output (commitment to pubkey, not to input) ● Tx can be bound to any output that matches <witness> and for which <witnessProg> yields true