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prasad-kumkar / PVM_Benchmark.md
Last active August 19, 2025 07:40
We benchmarked our JAM-compliant PVM with 13-register, 4GB memory on x86_64, comparing interpreter and AOT-based recompiler modes.

PVM Benchmarking [Draft 1]

Interpreter vs Recompiler vs EVM L1


This benchmark evaluates execution performance of JAM's Polkadot Virtual Machine (PVM) using two modes: an interpreter and an ahead-of-time (AOT) recompiler. All tests were performed on Tessera, a clean-room Python implementation of the PVM developed by ChainScore Labs. Benchmarks include synthetic (ADD_JUMP) and real-world (Conway's Game of Life) workloads.


ADD_JUMP Benchmark

@prasad-kumkar
prasad-kumkar / genomics_project.ipynb
Created November 26, 2021 13:05
Genomics_Project.ipynb
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pragma solidity ^0.5.1;
contract Context {
// Empty internal constructor, to prevent people from mistakenly deploying
// an instance of this contract, which should be used via inheritance.
constructor () internal { }
// solhint-disable-previous-line no-empty-blocks
function _msgSender() internal view returns (address payable) {
return msg.sender;
@prasad-kumkar
prasad-kumkar / contracts...Create2CloneFactory.sol
Created October 26, 2021 16:34
Created using remix-ide: Realtime Ethereum Contract Compiler and Runtime. Load this file by pasting this gists URL or ID at https://remix.ethereum.org/#version=soljson-v0.5.17+commit.d19bba13.js&optimize=true&runs=200&gist=
pragma solidity ^0.5.0;
// import "./metatx/NativeMetaTransaction.sol";
// import "./metatx/ContextMixin.sol";
import "./metatx/EIP712MetaTransaction.sol";
contract Create2CloneFactory is EIP712MetaTransaction
{
@prasad-kumkar
prasad-kumkar / contracts...Create2CloneFactory.sol
Created October 26, 2021 16:34
Created using remix-ide: Realtime Ethereum Contract Compiler and Runtime. Load this file by pasting this gists URL or ID at https://remix.ethereum.org/#version=soljson-v0.5.17+commit.d19bba13.js&optimize=true&runs=200&gist=
pragma solidity ^0.5.0;
// import "./metatx/NativeMetaTransaction.sol";
// import "./metatx/ContextMixin.sol";
import "./metatx/EIP712MetaTransaction.sol";
contract Create2CloneFactory is EIP712MetaTransaction
{
@prasad-kumkar
prasad-kumkar / contracts...Create2CloneFactory.sol
Created October 26, 2021 16:34
Created using remix-ide: Realtime Ethereum Contract Compiler and Runtime. Load this file by pasting this gists URL or ID at https://remix.ethereum.org/#version=soljson-v0.5.17+commit.d19bba13.js&optimize=true&runs=200&gist=
pragma solidity ^0.5.0;
// import "./metatx/NativeMetaTransaction.sol";
// import "./metatx/ContextMixin.sol";
import "./metatx/EIP712MetaTransaction.sol";
contract Create2CloneFactory is EIP712MetaTransaction
{
@prasad-kumkar
prasad-kumkar / Tutorial_Contribution_Description_Template.md
Last active August 23, 2021 08:41 — forked from yash-sharma1/Tutorial_Contribution_Description_Template.md
This Gist is a basic template for those who're interested in writing tutorials for Figment Learn. At the time of filling the form for writing tutorials applicants need to submit a link to their Gist file which contains initial details of the tutorial. On the basis of the details provided in Gist, we'll review the application for tutorial contrib…

How to Deploy Your Own Pallet: A Step by Step Guide

Overview of the Tutorial

With this tutorial, new para-chain developers would benefit for building custom pallets from scratch and adding that to their existing runtime. I am going to use a pallets template, modify and add custom functions to it, check for errors and give instructions about how to implement it. I love substrate framework, and would be very happy to help other developers get into substrate.

Who is this tutorial for?

Beginners into learning substrate framework, who has an understanding of blockchain runtime, storage, calls. And atleast has experience running the substrate node template with predefined pallets.

Technologies used in the Tutorial

import numpy as np
class ELM(object):
def __init__(self, inputSize, outputSize, hiddenSize):
"""
Initialize weight and bias between input layer and hidden layer
Parameters:
inputSize: int
The number of input layer dimensions or features in the training data