Godson-T缓存一致性协议的Murphi建模和验证

Godson-T缓存一致性协议是用于Godson-T众核处理器的缓存一致性协议．在Godson-T协议中,缓存一致性协议和存储一致性模型存在紧密的紧耦合关系,分析协议的一致性时发现该协议满足的缓存一致性不是强一致性,不满足传统意义上缓存透明的一致性要求．我们选取了Murphi模型检测工具作为我们建模的语言和验证工具．在对Godson-T缓存一致性协议建模的时候,由于协议的上述特点,我们需要对处理器核结点,高速缓存和内存作为一个整体建模,并成功地验证了协议的相关性质．     

申威众核处理器的并行NSGA-II算法

非支配排序遗传算法（NSGA-II）在多目标优化领域有着广泛的应用,但在处理复杂问题时运行时间相当长。并行化是提高算法执行速度的有效途径。众核处理器的出现,为实现高度并行奠定了物质基础。基于国产超算“神威·太湖之光”的申威众核处理器平台设计了并行NSGA-II算法（PNSGA-II）,实现了算法基于主核的一级并行和基于主/从核的二级并行。在典型测试函数集上的实验表明,在不影响解的质量前提下,PNSGA-II算法不仅大大加快了执行速度,同时算法的收敛速度也更快。     

Memory Efficient Two-Pass 3D Coprocessor FFT Algorithm for Intel（R） Xeon Phi TM

Equipped with 512-bit wide SIMD inst d large numbers of computing cores, the emerging x86-based Intel（R） Many Integrated Core （MIC） Architecture ot only high floating-point performance, but also substantial off-chip memory bandwidth. The 3D FFT （three-di fast Fourier transform） is a widely-studied algorithm; however, the conventional algorithm needs to traverse the three times. In each pass, it computes multiple 1D FFTs along one of three dimensions, giving rise to plenty of rided memory accesses. In this paper, we propose a two-pass 3D FFT algorithm, which mainly aims to reduce of explicit data transfer between the memory and the on-chip cache. The main idea is to split one dimension into ensions, and then combine the transform along each sub-dimension with one of the rest dimensions respectively erence in amount of TLB misses resulting from decomposition along different dimensions is analyzed in detail. el parallelism is leveraged on the many-core system for a high degree of parallelism and better data reuse of loc On top of this, a number of optimization techniques, such as memory padding, loop transformation and vectoriz employed in our implementation to further enhance the performance. We evaluate the algorithm on the Intel（R） PhiTM coprocessor 7110P, and achieve a maximum performance of 136 Gflops with 240 threads in offload mode, which ts the vendor-specific Intel（R）MKL library by a factor of up to 2.22X.     

Architecture and Evaluation of an Asynchronous Array of Simple Processors

This paper presents the architecture of an asynchronous array of simple processors (AsAP), and evaluates its key architectural features as well as its performance and energy efficiency. The AsAP processor calculates DSP applications with high energy-efficiency, is capable of high-performance, is easily scalable, and is well-suited to future fabrication technologies. It is composed of a two-dimensional array of simple single-issue programmable processors interconnected by a reconfigurable mesh network. Processors are designed to capture the kernels of many DSP algorithms with very little additional overhead. Each processor contains its own tunable and haltable clock oscillator, and processors operate completely asynchronously with respect to each other in a globally asynchronous locally synchronous (GALS) fashion. A 6×6 AsAP array has been designed and fabricated in a 0.18 μm CMOS technology. Each processor occupies 0.66 mm², is fully functional at a clock rate of 520–540 MHz at 1.8 V, and dissipates an average of 35 mW per processor at 520 MHz under typical conditions while executing applications such as a JPEG encoder core and a complete IEEE 802.11a/g wireless LAN baseband transmitter. Most processors operate at over 600 MHz at 2.0 V. Processors dissipate 2.4 mW at 116 MHz and 0.9 V. A single AsAP processor occupies 4% or less area than a single processing element in other multi-processor chips. Compared to several RISC processors (single issue MIPS and ARM), AsAP achieves performance 27–275 times greater, energy efficiency 96–215 times greater, while using far less area. Compared to the TI C62x high-end DSP processor, AsAP achieves performance 0.8–9.6 times greater, energy efficiency 10–75 times greater, with an area 7–19 times smaller. Compared to ASIC implementations, AsAP achieves performance within a factor of 2–5, energy efficiency within a factor of 3–50, with area within a factor of 2.5–3. These data are for varying numbers of AsAP processors per benchmark.

Cooperative Computing Techniques for a Deeply Fused and Heterogeneous Many-Core Processor Architecture

Due to advances in semiconductor techniques, many-core processors have been widely used in high performance computing. However, many applications still cannot be carried out e?ciently due to the memory...     

众核处理器片上同步机制和评估方法研究

同步机制是片上多核/众核处理器正确执行和协同通信的关键,其效率对处理器的性能非常重要.针对片上众核体系结构,提出并实现了两种粗粒度同步机制和一种细粒度同步机制,即片上专用硬件支持的同步机制、基于原语的片上互斥访问同步机制和基于满空标志位的细粒度同步机制;提出了粗粒度同步机制的评估标准和评估方法,并设计了量化评估程序.以片上同构众核处理器Godson-T模拟器和AMD Opteron商业片上多核处理器为平台,评估比较了提出的硬件支持的同步机制与基于原语的同步机制的性能.结果表明,硬件支持可以使得片上众核处理器的同步机制性能明显提高;在传统基于原语的同步机制中,大部分性能损失是由于负载不平衡和同步点的串行化操作而造成的等待时间.     

一种面向异构众核处理器的并行编译框架

异构众核处理器是面向高性能计算领域处理器发展的重要趋势,但其更为复杂的体系结构使得编程难的问题更加突出.针对这一问题,基于开源编译器Open64,提出了一种面向异构众核处理器的并行编译框架,将程序自动转换为异构并行程序.该框架主要包括4个模块：任务划分模块用来识别适合进行加速计算的程序段,实现了嵌套循环的多维并行识别方法;数据布局模块完成数据在主存和SPM之间的布局,实现了数组边界分析和指针范围分析;传输优化模块实现了数据传输合并、传输外提、打包传输、数组转置等多种数据传输优化方法;收益评估模块在构建代价模型的基础上实现了一种动静结合的收益评估方法.并且,基于SW26010处理器,对该编译框架进行了实现,测试结果表明,该编译框架能够实现一些程序以面向异构众核结构的并行变换,且获得较好的加速效果.     

基于申威众核处理器的圣维南求解程序的并行与优化

圣维南方程组可用于描述明渠非恒定流的汇流过程,在大规模水文模拟软件中,求该方程组的数值解是制约程序运行时间的最大瓶颈.通过分析串行程序结构及其计算热点,挖掘计算密集型程序中单步模拟循环计算段和指令排列等的可并行性,针对"神威·太湖之光"超级计算机的异构众核架构设计主从核异步并行方案,基于MPI和athread库对求解程...     

众核处理器片上网络的层次化全局自适应路由机制

Mesh和环拓扑结构以其实现简单、易于扩展的特点成为众核处理器片上网络应用最为广泛的拓扑结构.应用于Mesh结构中的健忘型路由算法在网络流量较大时影响片上网络的负载均衡,表现在降低吞吐量和增大数据包延迟.自适应算法中的本地自适应算法和区域自适应算法均存在不同程度的短视现象,不适合大规模的Mesh结构,而目前全局自适应算法又由于路由计算量大而速度缓慢.提出一种新的层次化全局自适应路由机制,包括一个全局拥塞信息传播网络Roof-Mesh和一个层次化全局自适应路由算法(global hierarchical adaptive routing algorithm, GHARA).通过全局拥塞信息传播网络得到拥塞信息,GHARA采用全网分区逐级计算路由的方式,减少了全局路由的计算步骤,从而减少了平均数据包延迟、提升了饱和带宽.实验结果表明GHARA表现优于其他区域和全局自适应路由算法.在人工注入通信模式下,8×8 Mesh平均饱和带宽比全局自适应算法GCA提高10.7%,16×16 Mesh平均饱和带宽比全局自适应算法GCA提高14.7%.在运行真实测试程序集SPLASH-2模式下,数据包延迟最高比GCA提高40%,平均提升14%.     

面向数据包处理的众核处理器核资源分配方法

众核处理器具有强大的并行处理能力,成为提升路由器转发性能的有效途径.基于众核处理器的数据包处理采用多级流水线结构,每个流水阶段的执行时间不同,要求分配不同的核数.已有的核资源均衡分配方法(equi-partition, EQUI)为每个流水阶段分配相同的核数,存在核资源浪费等缺点,限制了数据包处理性能.提出了一种众核处理器资源优化方法,即根据数据包的处理步骤将其划分成多个子阶段,通过统计各阶段的总执行时间,按执行时间比例分配给各个模块所需核数.与已有的EQUI相比,核资源最佳分配方法在数据包转发速率上提高了约20%.