Ionel Miu imiu

Architecture

Papers

Chips

An Energy-Efficient Configurable Lattice Cryptography Processor for the Quantum-Secure Internet of Things. ISSCC-2019
A 28nm Bulk-CMOS 4-to-8GHz ¡2mW Cryogenic Pulse Modulator for Scalable Quantum Computing. ISSCC-2019
A Scalable Quantum Magnetometer in 65nm CMOS with Vector-Field Detection Capability. ISSCC-2019
A 48GHz 5.6mW Gate-Level-Pipelined Multiplier Using Single-Flux Quantum Logic. ISSCC-2019

Resources

Performance of Flask, Tornado, GEvent, and their combinations

Wensheng Wang, 10/1/11

Source: http://blog.wensheng.org/2011/10/performance-of-flask-tornado-gevent-and.html

When choosing a web framework, I pretty much have eyes set on Tornado. But I heard good things about Flask and Gevent. So I tested the performance of each and combinations of the three. I chose something just a little more advanced than a "Hello World" program to write - one that use templates. Here are the codes:

1, Pure Flask (pure_flask.py)

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

So you're curious in learning this new thing called Reactive Programming, particularly its variant comprising of Rx, Bacon.js, RAC, and others.

Learning it is hard, even harder by the lack of good material. When I started, I tried looking for tutorials. I found only a handful of practical guides, but they just scratched the surface and never tackled the challenge of building the whole architecture around it. Library documentations often don't help when you're trying to understand some function. I mean, honestly, look at this:

Rx.Observable.prototype.flatMapLatest(selector, [thisArg])

Projects each element of an observable sequence into a new sequence of observable sequences by incorporating the element's index and then transforms an observable sequence of observable sequences into an observable sequence producing values only from the most recent observable sequence.

	#loading necessary libraries

	library(readr)
	library(dplyr)
	library(ggplot2)
	library(caret)
	library(kernlab)
	library(gridExtra)

	# naivebayes.txt
	#
	# sex height weight footsize
	# male 6 180 12
	# male 5.92 190 11
	# male 5.58 170 12
	# male 5.92 165 10
	# female 5 100 6
	# female 5.5 150 8
	# female 5.42 130 7

	# modification of https://gist.github.com/brendano/39760
	# automatically obtains data from the web
	# creates two data frames, test and train
	# labels are stored in the y variables of each data frame
	# can easily train many models using formula `y ~ .` syntax

	# download data from http://yann.lecun.com/exdb/mnist/
	download.file("http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz",
	"train-images-idx3-ubyte.gz")
	download.file("http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz",

	# -- coding: utf-8 --
	"""Parse Python source code and get or print docstrings."""

	__all__ = ('get_docstrings', 'print_docstrings')

	import ast

	from itertools import groupby
	from os.path import basename, splitext