Distributed Systems

/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.

Parallelism

/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.

Chapel

/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.

Intermediate Representation

/ˌaɪ ˈɑːr/

noun … “The shared language between source code and machines.”

IR, short for Intermediate Representation, is an abstract, structured form of code used internally by a Compiler to bridge the gap between high-level source languages and low-level machine instructions. It is not meant to be written by humans or executed directly by hardware. Instead, IR exists as a stable, analyzable format that enables transformation, optimization, and portability across languages and architectures.

Low Level Virtual Machine

/ˌɛl ɛl viː ɛm/

noun … “Reusable compiler infrastructure built for optimization.”

LLVM, short for Low Level Virtual Machine, is a modular compiler infrastructure designed to support the construction of programming language toolchains, advanced optimizers, and code generators. Rather than being a single compiler, LLVM is a collection of reusable components that can be assembled to build Compilers, static analysis tools, just-in-time systems, and ahead-of-time pipelines targeting many hardware architectures.

Graal

/ɡreɪl/

noun … “Optimizing compiler for the JVM ecosystem.”

Graal is a high-performance just-in-time (JIT) compiler and runtime component that targets the Java Virtual Machine. It replaces or supplements the traditional HotSpot JIT compiler to provide advanced optimizations, improved code generation, and support for dynamic languages on the JVM. By performing aggressive inlining, partial evaluation, and runtime profiling, Graal enhances execution speed and reduces memory overhead for both Java and polyglot workloads.