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the former is interleaved while the latter is not. A processor may support permute instructions, or strided load and store instructions, for moving between interleaved and non-interleaved representations. Interleaving has performance implications for cache coherency, ease of leveraging SIMD hardware, and leveraging a computer's addressing modes.
Programs may exhibit parallelism only, concurrency only, both parallelism and concurrency, neither. [6] Parallelism vs concurrency; Multi-threading and multi-processing (shared system resources) Synchronization (coordinating access to shared resources) Coordination (managing interactions between concurrent tasks)
Interleaved, preemptive, fine-grained or time-sliced multithreading are more modern terminology. In addition to the hardware costs discussed in the block type of multithreading, interleaved multithreading has an additional cost of each pipeline stage tracking the thread ID of the instruction it is processing.
In parallel computing, execution occurs at the same physical instant: for example, on separate processors of a multi-processor machine, with the goal of speeding up computations—parallel computing is impossible on a single processor, as only one computation can occur at any instant (during any single clock cycle).
Fine-grained (or interleaved) The main processor pipeline may contain multiple threads, with context switches effectively occurring between pipe stages (e.g., in the barrel processor). This form of multithreading can be more expensive than the coarse-grained forms because execution resources that span multiple pipe stages may have to deal with ...
One of the earliest examples of a barrel processor was the I/O processing system in the CDC 6000 series supercomputers. These executed one instruction (or a portion of an instruction) from each of 10 different virtual processors (called peripheral processors or PPs) before returning to the first processor. [1]
In computing, interleaved memory is a design which compensates for the relatively slow speed of dynamic random-access memory (DRAM) or core memory, by spreading memory addresses evenly across memory banks. That way, contiguous memory reads and writes use each memory bank in turn, resulting in higher memory throughput due to reduced waiting for ...
Due to the inherent difficulties in full automatic parallelization, several easier approaches exist to get a parallel program in higher quality. One of these is to allow programmers to add "hints" to their programs to guide compiler parallelization, such as HPF for distributed memory systems and OpenMP or OpenHMPP for shared memory systems.