Contemporary Languages in Parallel ComputingRaymond Hummel

Current Languages

Standard Languages• Distributed Memory Multiprocessors

MPI

• Shared Memory Multiprocessors OpenMP pthreads

• Graphics Processing Units CUDA OpenCL

MPI• Stands for: Message Passing Interface• Pros

Extremely Scalable Portable Can harness a multitude of hardware setups

• Cons Complicated Software Complicated Hardware Complicated Setup

MPI

OpenMP• Stands for: Open Multi-Processing• Pros

Incremental Parallelization Fairly Portable Simple Software

• Cons Limited Use-Case

OpenMP

POSIX Threads• Stands for: Portable Operating System Interface Threads• Pros

Portable Fine Grained Control

• Cons All-or-Nothing Complicated Software Limited Use-Case

POSIX Threads

CUDA• Stands for: Compute Unified Device Architecture• Pros

Manufacturer Support Low Level Hardware Access

• Cons Limited Use-Case Only Compatible with NVIDIA Hardware

CUDA

OpenCL• Stands for: Open Compute Language• Pros

Portability Heterogeneous Platform Works with All Major Manufacturers

• Cons Complicated Software Special Tuning Required

Future Languages

Developing Languages• D • Rust• Harlan

D• Performance of Compiled Languages• Memory Safety• Expressiveness of Dynamic Languages• Includes a Concurrency Aware Type-System• Nearing Maturity

Rust• Designed for creation of large Client-Server Programs on the Internet• Safety• Memory Layout• Concurrency• Still Major Changes Occurring

Harlan• Experimental Language• Based on Scheme• Designed to take care of boilerplate for GPU Programming• Could be expanded to include automatic scheduling for both CPU and

GPU, depending on available resources.

Questions?