Lecture 1: Introduction to Research — [📝Lecture Notebooks] [
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[
What is strict aliasing? First we will describe what is aliasing and then we can learn what being strict about it means.
In C and C++ aliasing has to do with what expression types we are allowed to access stored values through. In both C and C++ the standard specifies which expression types are allowed to alias which types. The compiler and optimizer are allowed to assume we follow the aliasing rules strictly, hence the term strict aliasing rule. If we attempt to access a value using a type not allowed it is classified as undefined behavior(UB). Once we have undefined behavior all bets are off, the results of our program are no longer reliable.
Unfortunately with strict aliasing violations, we will often obtain the results we expect, leaving the possibility the a future version of a compiler with a new optimization will break code we th
cmake_minimum_required(VERSION 2.8.4) | |
project(py1) | |
find_package(PythonLibs REQUIRED) | |
include_directories(${PYTHON_INCLUDE_DIRS}) | |
ADD_DEFINITIONS( -std=c++11 ) | |
set(SOURCE_FILES main.cpp) |
from celery import Task | |
from celery.task import task | |
from my_app.models import FailedTask | |
from django.db import models | |
@task(base=LogErrorsTask) | |
def some task(): | |
return result | |
class LogErrorsTask(Task): |
I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.
I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real