zommiommy

zommiommy

#![no_std]
extern crate alloc;
use alloc::vec::Vec;
use primitive::Primitive;

/// Implementation of:
/// > An Efficient Representation for Sparse Sets
/// > by Preston Briggs and Linda Torczon
/// > <https://dl.acm.org/doi/pdf/10.1145/176454.176484>
/// > <https://research.swtch.com/sparse>

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//! Implementation of SipHash from [Jean-Philippe Aumasson](https://www.aumasson.jp/) and Daniel J. Bernstein.
//!
//! SipHash is a general-purpose hashing function: it runs at a good
//! speed (competitive with Spooky and City) and permits strong _keyed_
//! hashing. This lets you key your hash tables from a strong RNG, such as
//! [`rand::os::OsRng`](https://docs.rs/rand/latest/rand/rngs/struct.OsRng.html).
//!
//! Although the SipHash algorithm is considered to be generally strong,
//! it is not intended for cryptographic purposes. As such, all
//! cryptographic uses of this implementation are _strongly discouraged

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/// A simple online linear regression algorithm.
/// See https://en.wikipedia.org/wiki/Simple_linear_regression#Fitting_the_regression_line
/// for details.
pub struct FirstOrderOLS {
    x: f64,
    y: f64,
    xx: f64,
    xy: f64,
    n: usize,

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#![feature(test)]
extern crate test;

use test::{black_box, Bencher};
// Optionally include some setup
const NUMBER_OF_ELEMENTS: usize = 10_000;
const BITS: usize = 5;

fn gen_data() -> Vec<u8> {
    let mut res = Vec::with_capacity(NUMBER_OF_ELEMENTS);

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#![deny(unconditional_recursion)]
use core::fmt::{Debug, Display, LowerHex, Binary}; 
use core::ops::*;
use core::sync::atomic::*;
use core::num::*;


/// Trait of operations possible on both Signed and Unsiged words
pub trait Number: Sized + Send + Sync +
    Display + LowerHex +

zommiommy

# Version of Elastic products
STACK_VERSION=8.4.2

# Port to expose Elasticsearch HTTP API to the host
ES_PORT=9200

# Port to expose Kibana to the host
KIBANA_PORT=5601

# RAM for each service 4GB

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import struct

def u32(data):
    return struct.unpack("i", data)[0]

def p32(data):
    return struct.pack("i", data)

class Regs:
    IP = 0

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import time
import numpy as np
from tqdm.auto import trange
import matplotlib.pyplot as plt
from optimizers import SGD, Momentum, Adam, Nadam

# Generate some data
positives = np.random.normal(loc=-0.3, size=1000)
negatives = np.random.normal(loc=0.0, size=1000)

zommiommy

#![feature(portable_simd)]
#![feature(test)]

extern crate test;
use test::{black_box, Bencher};
use std::convert::TryInto;
use std::simd::*;
use std::arch::x86_64::*;

type Reg = f32x8;