subhasis maity maitysubhasis

##Google Interview Questions: Product Marketing Manager

Why do you want to join Google? -- Because I want to create tools for others to learn, for free. I didn't have a lot of money when growing up so I didn't get access to the same books, computers and resources that others had which caused money, I want to help ensure that others can learn on the same playing field regardless of their families wealth status or location.
What do you know about Google’s product and technology? -- A lot actually, I am a beta tester for numerous products, I use most of the Google tools such as: Search, Gmaill, Drive, Reader, Calendar, G+, YouTube, Web Master Tools, Keyword tools, Analytics etc.
If you are Product Manager for Google’s Adwords, how do you plan to market this?
What would you say during an AdWords or AdSense product seminar?
Who are Google’s competitors, and how does Google compete with them? -- Google competes on numerous fields: --- Search: Baidu, Bing, Duck Duck Go

Introduction

This gist started with a collection of resources I was maintaining on stream data processing — also known as distributed logs, data pipelines, event sourcing, CQRS, and other names.

Over time the set of resources grew quite large and I received some interest in a more guided, opinionated path for learning about stream data processing. So I added the reading list.

Please send me feedback!

The natural way to start with CUDA

The natural way to start with CUDA if you plan to be self taught is:

CUDA by Example: An Introduction to General-Purpose GPU Programming by Jason Sanders and Edward Kandrot Nice introduction. It is more like playing with your GPU and admire its capabilities.
Programming Massively Parallel Processors, Second Edition: A Hands-on Approach by David B. Kirk and Wen-mei W. Hwu It explains a lot of things in GPU Programming. You simply can't go without it.

What forces layout / reflow

All of the below properties or methods, when requested/called in JavaScript, will trigger the browser to synchronously calculate the style and layout*. This is also called reflow or layout thrashing, and is common performance bottleneck.

Generally, all APIs that synchronously provide layout metrics will trigger forced reflow / layout. Read on for additional cases and details.

Element APIs

Getting box metrics

elem.offsetLeft, elem.offsetTop, elem.offsetWidth, elem.offsetHeight, elem.offsetParent

	#define _XOPEN_SOURCE 500 /* Enable certain library functions (strdup) on linux. See feature_test_macros(7) */

	#include <time.h>
	#include <stdlib.h>
	#include <stdio.h>
	#include <limits.h>
	#include <string.h>
	#include <assert.h>

	struct avl_node_s {

	// In View Class

	- (void)drawRect:(CGRect)dirtyRect
	{
	// Draw the background
	NSGraphicsContext* theContext = [NSGraphicsContext currentContext];
	[theContext saveGraphicsState];
	[[NSGraphicsContext currentContext] setPatternPhase:NSMakePoint(0,[self.superview bounds].size.height)];
	[_backgroundColor set];
	NSRectFill([self bounds]);

	Latency Comparison Numbers (~2012)
	----------------------------------
	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

	console.log('Loading function');

	var AWS = require('aws-sdk');
	AWS.config.region = 'us-west-2';

	exports.handler = function(event, context) {
	console.log("\n\nLoading handler\n\n");
	var sns = new AWS.SNS();

	sns.publish({

	#Backpropagation algorithm written in Python by annanay25.
	import string
	import math
	import random

	class Neural:
	def __init__(self, pattern):
	#
	# Lets take 2 input nodes, 3 hidden nodes and 1 output node.
	# Hence, Number of nodes in input(ni)=2, hidden(nh)=3, output(no)=1.

	// How to build: "CC=clang go build"

	package main

	import (
	"fmt"
	"net/url"
	"strconv"
	"unsafe"
	)