Software

/ˈpæk.sɒs/

noun … “Consensus algorithm for unreliable networks.”

Paxos is a fault-tolerant Consensus algorithm designed to achieve agreement among nodes in a Distributed System, even when some nodes fail or messages are delayed or lost. It ensures that a single value is chosen and consistently replicated across all non-faulty nodes, providing a foundation for reliable state machines, replicated databases, and coordination services.

/kənˈsɪstənsi/

noun … “All nodes see the same data at the same time.”

/əˌveɪləˈbɪləti/

noun … “System responds to requests, even under failure.”

/ˈpɑːrtɪʃən ˈtɒlərəns/

noun … “System keeps working despite network splits.”

/kənˈsɛnsəs/

noun … “Agreement among distributed nodes.”

Consensus is the process by which multiple nodes in a Distributed System agree on a single value or state despite failures, message delays, or node crashes. Consensus ensures that all non-faulty nodes make consistent decisions, which is crucial for maintaining data integrity, coordinating actions, and implementing replicated state machines. It underpins critical operations in databases, blockchain networks, and fault-tolerant services.

/kæp ˈθiərəm/

noun … “You can only fully guarantee two out of three.”

/dɪˈstrɪbjʊtɪd ˈsɪstəmz/

noun … “Independent computers acting as one system.”

Distributed Systems are computing systems composed of multiple independent computers that communicate over a network and coordinate their actions to appear as a single coherent system. Each component has its own memory and execution context, and failures or delays are expected rather than exceptional. The defining challenge of distributed systems is managing coordination, consistency, and reliability in the presence of partial failure and unpredictable communication.

/ˈpærəˌlɛlɪzəm/

noun … “Doing multiple computations at the same time.”

Parallelism is a computing model in which multiple computations or operations are executed simultaneously, using more than one processing resource. Its purpose is to reduce total execution time by dividing work into independent or partially independent units that can run at the same time. Parallelism is a core technique in modern computing, driven by the physical limits of single-core performance and the widespread availability of multicore processors, accelerators, and distributed systems.

/ˈtʃæpəl/

noun … “Parallel programming language designed for scalable systems.”

Chapel is a high-level programming language designed specifically for parallel computing at scale. Developed by Cray as part of the DARPA High Productivity Computing Systems initiative, Chapel aims to make parallel programming more productive while still delivering performance competitive with low-level approaches. It is intended for systems ranging from single multicore machines to large distributed supercomputers.

/ˈfʌŋkʃən/

noun … “Reusable block that maps inputs to outputs.”