What is a Thread?

A thread is a term that denotes the execution of the smallest sequence of programmed instructions that can be managed by a scheduler1. Typically, a thread is used by an operating system, and is a component of a process.

Properties of threads:

  • Multiple threads can exists within one process (multithreading)
  • By property, it can execute concurrently and shares resources (ie. memory)

It is not a process

Though the definition uses the word process, a thread is not a process, vice versa. However, we can say that a thread or multiple threads is contained within a subset of a process.

  • processes are typically independent
  • processes carry more state information than threads, while multiple threads within a process share process state as well as memory & other resources
  • processes have separate address spaces2, threads share theirs
  • processes interact only through system-provided inter-process communication3 mechanisms
  • context-switching with threads is faster than it is with processes


This is the term to denote the processing of one command at a time.


This allows multiple threads to exist within the context of one process. They share the process’s resources, but are able to execute independently. It can also be useful for concurrent execution or parallel execution4.

Where does JavaScript fit on the binary?

JavaScript is an example of non-parallel concurrency. There is only one thread. Any asynchronous callback must wait until the previous chunk of code has finished executing. This is important to know, because it guarantees that any function you write is atomic5, and thus, no callback can interrupt the function until it returns.

The atomization of JavaScript functions, guarantees that the shared memory will use the entire data as it appears in the moment of execution.

There is one single thread that handles your event loop6. The event loop is a queue of unprocessed events. It iterates through one at a time, and invokes each event as necessary; say a function calls another function, there is no other function you can implement in your program that can block that callback from executing. Once an event is processed, the event loop dequeues that event and the process continues.

Synchronous I/O (blocking I/O)

A form of I/O that waits for each process to complete before starting the next. This approach blocks the progress of a program while the communication is in progress, leaving system resources idle. If there are many I/O operations, a processor can spend much of it’s time idle, waiting for I/O operations to complete.

Asynchronous I/O (non-blocking I/O, non-sequential I/O)

A form of I/O that permits other processing to continue before the transmission has finished. It functions such that any operation that depends on another operation to complete to remain blocked, while other functions that are independent to continue.

The method for implementation utilizes polling7 at intervals

This is used to improve throughput, latency, and/or responsiveness.

What is Node.js, then?

Node.js is a runtime environment7 for JavaScript. It operates on a single-thread and uses non-blocking I/O calls. If you recall, this will support concurrency between function calls, and the single thread enforces callbacks.

While this sounds inefficient, node.js operates asynchronously. Which is why we can say that it is event-driven. The event loop exists to poll specific events and invokes handlers at the proper time. A callback function is also known as an event handler.

So when a function is invoked in the event pool from Node.js it makes that request and attaches a callback function to that request. Whenever the request is fulfilled, an event is emitted to trigger the associated callback to do something with either the results of the requested action

In order to accomodate the single-threaded event loop, libuv is utilized to use a fixed-size threadpool, which is responsible for some of the non-blocking asynchronous I/O operations.

Uses of Node include:

  • Web servers and networking tools
  • file system I/O
  • networking (DNS, HTTP, TCP, TLS/SSL, or UDP)
  • binary data (buffers)
  • cryptography functions
  • data streams

More on Threadpool

Since each execution of parallel tasks are handled by the threadpool, let’s look a little closer to what that means.

A threadpool is a queued set of threads that is dispatched by the main thread. Each thread differs inherent to its type; networking is non-blocking and file I/O runs in a blocking way.

When a thread in the thread pool completes a task, it informs the main thread of this, which in turn, the main thread reacts by executing the registered callback. Callbacks are handled serially on the main thread, which may pose problems if long-lasting computations will freeze the entire event-loop.

Glossary: Throughput - the total amount of work completed per time unit Response Time - time from work becoming enabled until the first point it begins execution Latency - the time between working becoming enabled and its completion Heap - Denotes a large, mostly unstructured, region of memory Data race - Two memory accesses in a program where both:

  • target the same location
  • are performed concurrently by two threads
  • are not reads
  • are not synchronization operations Data races can exist without race conditions but many data races lead to race conditions. Race condition - Where output is dependent on the sequence of timing of other unctonrollable events. Race conditions can exist without data races, but many race conditions are due to data races. Execution Model - Specifies how work takes place specific to the language

Resources: https://en.wikipedia.org/wiki/Thread_(computing) https://en.wikipedia.org/wiki/Scheduling_(computing) https://en.wikipedia.org/wiki/Parallel_computing https://en.wikipedia.org/wiki/Linearizability https://en.wikipedia.org/wiki/Asynchronous_I/O https://en.wikipedia.org/wiki/Runtime_system https://en.wikipedia.org/wiki/Node.js https://en.wikipedia.org/wiki/Observer_pattern https://developer.mozilla.org/en/docs/Web/JavaScript/EventLoop http://softwareengineering.stackexchange.com/questions/190719/ https://www.quora.com/How-does-a-single-thread-handle-asynchronous-code-in-JavaScriptthe-difference-between-concurrent-and-parallel-execution http://preshing.com/20130618/atomic-vs-non-atomic-operations/ http://blog.regehr.org/archives/490


  1. A scheduler is a method by which work is assigned to resources to complete that work. 

  2. An address space defines a range of discrete addresses; of each may relate to a network host, peripheal device, disk sector, a memory cell or other logical/physical idenitty. 

  3. IPC are mechanisms that allow processes to share data; typically categorized as clients and servers. 

  4. The difference between concurrent and parallel execution is explained as concurrency being the sequence of task A and task B happening independently. Such that task A begins, and then B starts before task A is finished. Otherwise stated that A and B tasks/calculations happen within the same time frame, with a general tendency towards depdendency between the two.

    On the other hand, parallelism describes two or more tasks/calculations that happen simultaneously. Parallelism is one way to implement concurrency. This is seen through task switching; the CPU will switch between tasks A and B with fractions of time slices in between and the two tasks will appear to be running in parallel. 

  5. This is a term used in concurrent programming. Also known as linearizability. An operation (or set of) is atomic if it appears to the rest of the system to occur instantaneously. It guarantees isolation from concurrent processes. They commonly have a succeed-or-fail definition. They either successfully change the state of the system or have no apparent effect. 

  6. Got its name from its usual implementation:

    while(queue.waitForMessage()) {

    queue.processNextMessage waits synchronously for a message to arrive (where a message is an association with the function to be called in a JavaScript runtime).

    Each message is processed completely before any other message is processed. It cannot be pre-empted and will run entirely before any other code runs. Unlike in C, which if a function runs in a thread, it can be stopped at any point to run some other code in another thread. 

  7. A system to implement an execution model (the order in which work was specified in terms of the language that it gets performed.)  2