What is fault tolerance and how does it help parallel programming?

1 Sources of faults

Parallel systems are prone to various kinds of faults that can occur at different levels of the hardware or software stack, such as hardware failures, software bugs, environmental factors, and human errors. Hardware failures can be transient, intermittent, or permanent and can cause data loss, corruption, or inconsistency. Software bugs can result in incorrect or unexpected behavior, memory leaks, deadlocks, or crashes. Environmental factors can cause hardware failures, network congestion, or security breaches. Finally, human errors can cause software bugs, data loss, or unauthorized access.

2 Types of faults

Faults can be divided into various types based on their impact on the parallel program and the system. Common examples include fail-stop faults, which cause a processor or machine to completely and permanently stop functioning, making them easy to detect and handle. Byzantine faults, on the other hand, cause processors or machines to behave maliciously, sending incorrect messages or data to other processors. These faults are hard to detect and handle due to their ability to compromise the correctness and security of the system. Crash faults lead to a processor or machine ceasing its operations temporarily or intermittently, but without affecting its state or output. These are more common than fail-stop faults as they can be caused by transient hardware failures, software bugs, or environmental factors. Finally, silent faults cause processors or machines to produce incorrect output without crashing or stopping; also known as silent data corruption (SDC) faults, they can corrupt the data or results of a parallel program and are difficult to detect and handle due to potential hardware failures, software bugs, or environmental factors.

4 Techniques for fault tolerance

Fault tolerance is the ability of a parallel program or a system to continue functioning correctly despite the presence of faults. To achieve this, various techniques can be employed, such as redundancy, checkpointing, and replication. Redundancy involves using extra resources or components to increase reliability or availability; this can be applied at hardware, software, data, or computation levels. Checkpointing involves saving the state or data of the parallel program or system at regular intervals; this can be done at application, library, or system level. Replication entails creating and maintaining multiple copies of the parallel program or system; this can be done at task, process, or machine level. All these techniques can be used to prevent, detect, or recover from faults.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?