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| 1 | Efficient and flexible memory architecture to alleviate data and context bandwidth bottlenecks of coarse-grained reconfigurable arrays显示文摘The computational capability of a coarse-grained reconfigurable array(CGRA)can be significantly restrained due to data and context memory bandwidth bottlenecks.Traditionally,two methods have been used to resolve this problem.One method loads the context into the CGRA at run time.This method occupies very small on-chip memory but induces very large latency,which leads to low computational efficiency.The other method adopts a multi-context structure.This method loads the context into the on-chip context memory at the boot phase.Broadcasting the pointer of a set of contexts changes the hardware configuration on a cycle-by-cycle basis.The size of the context memory induces a large area overhead in multi-context structures,which results in major restrictions on application complexity.This paper proposes a Predictable Context Cache(PCC)architecture to address the above context issues by buffering the context inside a CGRA.In this architecture,context is dynamically transferred into the CGRA.Utilizing a PCC significantly reduces the on-chip context memory and the complexity of the applications running on the CGRA is no longer restricted by the size of the on-chip context memory.Data preloading is the most frequently used approach to hide input data latency and speed up the data transmission process for the data bandwidth issue.Rather than fundamentally reducing the amount of input data,the transferred data and computations are processed in parallel.However,the data preloading method cannot work efficiently because data transmission becomes the critical path as the reconfigurable array scale increases.This paper also presents a Hierarchical Data Memory(HDM)architecture as a solution to the efficiency problem.In this architecture,high internal bandwidth is provided to buffer both reused input data and intermediate data.The HDM architecture relieves the external memory from the data transfer burden so that the performance is significantly improved.As a result of using PCC and HDM,experiments running mainstream video decoding programs achieved performance improvements of 13.57%–19.48%when there was a reasonable memory size.Therefore,1080p@35.7fps for H.264high profile video decoding can be achieved on PCC and HDM architecture when utilizing a 200 MHz working frequency.Further,the size of the on-chip context memory no longer restricted complex applications,which were efficiently executed on the PCC and HDM architecture. | YANG Chen LIU Lei Bo YIN Shou Yi WEI Shao Jun | 2014 | Science China(Physics,Mechanics & Astronomy)2014，57，12： | 2 |
| 2 | vSpec: workload-adaptive operating system specialization for virtual machines in cloud computing显示文摘In general, operating systems(OSs) are designed to mediate access to device hardware by applications. They process different kinds of system calls using an indiscriminate kernel with the same configuration.Applications in cloud computing platforms are constructed from service components. Each of the service components is assigned separately to an individual virtual machine(VM), which leads to homogeneous system calls on each VM. In addition, the requirements for kernel function and configuration of system parameters from different VMs are different. Therefore, the suit-to-all design incurs an unnecessary performance overhead and restricts the OS's processing capacity in cloud computing. In this paper, we propose an adaptive model for cloud computing to resolve the conflict between generality and performance. Our model adaptively specializes the OS of a VM according to the resource-consuming characteristics of workloads on the VM. We implement a prototype of the adaptive model, v Spec. There are five classes of VM: CPU-intensive, memory-intensive, I/O-intensive, networkintensive and compound, according to the resource-consuming characteristics of the workloads running on the VMs. v Spec specializes the OS of a VM according to the VM class. We perform comprehensive experiments to evaluate the effectiveness of v Spec on benchmarks and real-world applications. | Xinkui ZHAO Jianwei YIN Zuoning CHEN Sheng HE | 2016 | Science China(Information Sciences)2016，59，9： | 0 |
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