achille

Context:
https://gist.github.com/achille/d1eadf82aa54056b9ded7706e8f56760
https://chatgpt.com/share/6959ed27-accc-800e-8e87-21aa81e93c07

Claude Benchmark: 
Config: Moderate (150,100) - CORRECT SOLUTIONS ONLY
────────────────────────────────────────────────────────────────────────────────
  Method                  Time       max_err    wrong/20000
  ─────────────────────────────────────────────────────────────────────────────
  faded_opt (2 iter)      30.1 ns    0.18       0  ✅

achille

Context:
https://gist.github.com/achille/d1eadf82aa54056b9ded7706e8f56760

Chatgpt pro: run
https://chatgpt.com/share/6959ed27-accc-800e-8e87-21aa81e93c07

Benchmarks by Claude:

Method                    Time     Iters  sqrt/iter  Accurate?  Notes
  -------------------------------------------------------------------------------

achille

Context:
https://news.ycombinator.com/reply?id=46483541

Implementations: 
https://claude.ai/share/428502a2-81f0-421d-a3d7-08bceb96d039
https://chatgpt.com/share/6959ed27-accc-800e-8e87-21aa81e93c07


Eval: 
https://claude.ai/share/98dc0a03-0d03-4053-8460-3fb7b2b2676d

achille

// compactness() calculates how closely the resulting documents are located together
// It counts the size of the documents vs size of the unique pages they reside on
 
function compactness(collection, query, limit) {
    Object.size = function(o) { var size = 0, key;
        for (key in o) { if (o.hasOwnProperty(key)) size++; }
        return size; };
 
    count=0;
    size=0;

achille

import numpy as np
import scipy.optimize as spo
ir = lambda n: int(round(n))

# Constants
s_freq = 500   #server-server heartbeat frequency ms
c_freq = 10000 #client-server heartbeat frequency ms

# Simulation boundaries
threshold = 300000 # 5 minute max lag/skew

achille

/* 
 * Auto-tuning delete that allows for removal of large amounts of data 
 * without impacting performance. Configurable to a target load amount.
 *
 * How it works: 
 * TL;DR: Delete a small slice every second; Vary the size of each slice 
 *        based on how long the previous delete took; sleep; repeat. 
 *
 * TODO: Modify this to allow for deletion based on objectid's date 
 *       which is embedded in the first four bytes.

achille

/* Check for gaps or duplicates in keyspace */

function check_keyspace(ns) { 
    print("Checking: " + ns);
    str = JSON.stringify
    forwardCount=0;
    reverseCount=0;
    min = db.chunks.find(ns).pretty().sort({min: 1}).limit(1)[0]
    max = db.chunks.find(ns).pretty().sort({min:-1}).limit(1)[0]
    current = min

achille

Howdy folks

This is an attempt at standardizing the intro threads, and instructions on how to include a student map in them. Note the map & question set may be added to existing Piazza threads.

Steps:

Create a Google Map

• Login to Google Maps, create a new Map
• Menu -> Your Places -> Maps -> Create Map

achille

"""
Vitter JS (1987) 'An efficient algorithm for sequential
random sampling.' ACM T. Math. Softw. 13(1): 58--67.

Copied from: https://gist.github.com/ldoddema/bb4ba2d4ad1b948a05e0
"""

from math import exp, log
import random
import numpy as np

achille

//Create 1gb collection & enqueue
for(i=0;i<1000;i++){db.foo.insert({f:''.pad(1024*1024,true,'A')})}
enqueueWork("test.foo")

//Each worker calls dequeue() and works on it's own range
work = dequeue("test.foo")


function enqueueWork(ns,splitSizeBytes=320000000){
    split = db.runCommand({splitVector:ns, keyPattern:{_id: 1},