并行处理[2]是解决大规模图形图像处理问题的有效手段,但由于体积大、功耗高和难以维护等特点,使以多处理系统为代表的很多图形图像处理系统难以得到广泛应用[3]。多态并行处理器实现了单指令多数据(SIMD)和多指令多数据(MIMD)计算模式的混合,其结构简单,功耗低,同时在阵列机上分区并发实现该两种模式,并且能够在两种模式间实现一步转换
In this SIMD parallel computing device, an address line is used that is common to N groups. Batch access (parallel access) for all groups is executed to the memory cells indicated by the address line in each of the memory cell groups of the N groups. With this configuration, the ...
随着并行计算和集成电路的不断发展,如何有效地提高处理器的并行处理性能已经成为热点问题。传统处理器通过开发指令级并行(Instruction Level Parallelism,ILP)[1]来提高处理器的性能,但硬件的复杂度及功耗等因素影响了处理器的性能。因此设计者们纷纷把目光投向更高层次的线程级并行(Thread Level Parallelism,TLP)[1-3]...
In this installment, we circle back to delve deeper into SIMD and MIMD architectures, fundamental pillars of parallel computing. These architectures are the cornerstone upon which several parallel programming models are built. The evolution of these models closely mirrors advancements in comput...
But many programs are not that parallel. And in modern world, these who are that parallel don't run on CPUs, GPGPUs are more suitable for them and have way more compute power. 一个明显的方法是增加处理器,即增加核心数量。但是许多程序并不是那么并行化。而且在现代世界中,那些并行化程度较高的...
This method could organize and partition the reconstruction data effectively, which enables accessing memory continuously and makes it easy to implement theSIMDtechnique on data parallel computing. 主要从传统FDK算法的改进和数据并行计算两方面来研究快速三维图像重建算法,提出了一种Z线优先重建法,能够有效地组...
In SIMD, elements of short vectors are processed in parallel. In SMT, instructions of several threads are run in parallel. SIMT is somewhere in between – an interesting hybrid between vector processing and hardware threading. My presentation of SIMT is focused on hardware architecture and its imp...
In a SIMD architecture, each instruction applies the same operation in parallel across many data elements. SIMD is typically implemented using processors with vector registers and execution units; a scalar thread issues vector instructions that execute in SIMD fashion. In a SIMT architecture, rather ...
In order to adapt SIMD machine to more flexible SPMD paradigm for MIMD machine, a new branching mechanism is introduced.doi:10.1016/S0927-5452(98)80023-3Yoshizo Takahashi aMasahiko Sano aTornio Inoue aAdvances in Parallel Computing
It is important to understand thatmd5-simddoes not speed upa single threaded MD5 hash sum. Rather it allows multipleindependentMD5 sums to be computed in parallel on the same CPU core, thereby making more efficient usage of the computing resources. ...