byronyi

/*
* Space complexity: O(1); Time complexity: O(n).
*/
void reverseString(char* str){
  if(str == NULL) return; // Validation checking.
  if(*str == "\0") return; // Empty string.
  
  char temp; // For swapping tail and head.
  
  char* head=str, tail=str; // Pointers for the beginning and the end of the string.

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### MATPLOTLIBRC FORMAT

# This is a sample matplotlib configuration file - you can find a copy
# of it on your system in
# site-packages/matplotlib/mpl-data/matplotlibrc.  If you edit it
# there, please note that it will be overridden in your next install.
# If you want to keep a permanent local copy that will not be
# over-written, place it in HOME/.matplotlib/matplotlibrc (unix/linux
# like systems) and C:\Documents and Settings\yourname\.matplotlib
# (win32 systems).

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# Author: Vlad Niculae <vlad@vene.ro>
# Licence: BSD

from __future__ import division, print_function
import numpy as np
from sklearn.utils import check_random_state


class SquaredLoss(object):
    def loss(self, y, pred):

byronyi

Gartner:
https://www.gartner.com/doc/2867017/-planning-guide-overview-architecting
https://www.gartner.com/doc/2929317/framework-evaluating-big-data-initiatives
https://www.gartner.com/doc/2773117/security-futures-plan-peak-threat
https://www.gartner.com/doc/2691917/big-data-needs-datacentric-security
https://www.gartner.com/doc/2621115/big-data-analytics-requires-ethical

Books and Training:
http://www.amazon.com/Data-Science-Big-Analytics-Discovering/dp/111887613X
http://www.kaggle.com/competitions#getting-started

byronyi

import itertools
from operator import itemgetter

def iunzip(iterable):
    """Iunzip is the same as zip(*iter) but returns iterators, instead of 
    expand the iterator. Mostly used for large sequence"""

    _tmp, iterable = itertools.tee(iterable, 2)
    iters = itertools.tee(iterable, len(_tmp.next()))
    return (itertools.imap(itemgetter(i), it) for i, it in enumerate(iters))

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#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <libgen.h>
#include <signal.h>

#include <err.h>
#include <assert.h>

#include <zmq.h>

byronyi

#System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

##Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

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Testing Gluster RDMA with Soft-iWARP

There’s a Gluster 3.4 RDMA test day right around the corner, and I want to join in on the fun. The trouble is, I don’t have any RDMA-capable hardware in my lab right now. Undaunted, I hit the Web in search of a software-based solution, one that would at least allow me to run through the tests.

I found a pair of promising-looking options:

• Soft-iWARP

• Soft ROCE

The information out on the web about these projects is a bit thinner than I’d like, but I found a blog post howto on installing Soft-iWARP on Ubuntu 10.10 and another for Debian 6 and figured I’d try it out on Fedora 18.

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Latency Comparison Numbers
--------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

byronyi

"""Benchmark tensorflow distributed by adding vector of ones on worker2
to variable on worker1 as fast as possible.

On 2014 macbook, TensorFlow 0.10 this shows

Local rate:       2175.28 MB per second
Distributed rate: 107.13 MB per second

"""