Table of Contents
What is parallel and distributed computing research?
The parallel and distributed computing is concerned with concurrent use of multiple compute resources to enhance the performance of a distributed and/or computationally intensive application. The compute resources may be a single computer or a number of computers connected by a network.
What is HPC and GPU?
GPU computing is the use of a GPU (graphics processing unit) as a co-processor to accelerate CPUs for general-purpose scientific and engineering computing. There are a number of GPU-accelerated applications that provide an easy way to access high-performance computing (HPC).
What is parallel processing in HPC?
Task parallelism involves the decomposition of a task into sub-tasks and then allocating each sub-task to a processor for execution. The processors would then execute these sub-tasks concurrently and often cooperatively. Task parallelism does not usually scale with the size of a problem.
What are the issues in parallel and distributed computing?
Important concerns are workload sharing, which attempts to take advantage of access to multiple computers to complete jobs faster; task migration, which supports workload sharing by efficiently distributing jobs among machines; and automatic task replication, which occurs at different sites for greater reliability.
Why are GPUs used for HPC?
GPUs have the potential to significantly reduce space, power and cooling demands, and reduce the number of operating system images that must be managed relative to traditional CPU-only clusters of similar aggregate computational capability.
What are the types of parallel processing?
The three models that are most commonly used in building parallel computers include synchronous processors each with its own memory, asynchronous processors each with its own memory and asynchronous processors with a common, shared memory.
What are HPC systems?
High performance computing (HPC) is the ability to process data and perform complex calculations at high speeds. One of the best-known types of HPC solutions is the supercomputer. A supercomputer contains thousands of compute nodes that work together to complete one or more tasks. This is called parallel processing.
Why GPU for HPC?
Why GPU for HPC? •Graphics Processing Units(GPUs) were originally designed to accelerate graphics tasks like image rendering. •They became very very popular with video gamers, because they’ve produced better and better images, and lightning fast.
What is an accelerator in HPC?
•In HPC, an accelerator is hardware component whose role is to speed up some aspect of the computing workload. •In the olden days (1980s), supercomputers sometimes had array processors, which did vector operations on arrays
What are graphics processing units (GPUs)?
•Graphics Processing Units(GPUs) were originally designed to accelerate graphics tasks like image rendering. •They became very very popular with video gamers, because they’ve produced better and better images, and lightning fast. •And, prices have been extremely good, ranging from three figures at the low end to four figures at the high end.