Huizhan Yi

Optimizing linpack benchmark on GPU-accelerated petascale supercomputer

In this paper we present the programming of the Linpack benchmark on TianHe-1 system, the first petascale supercomputer system of China, and the largest GPU-accelerated heterogeneous system ever attempted before. A hybrid programming model consisting of MPI, OpenMP and streaming computing is described to explore the task parallel, thread parallel and data parallel of the Linpack. We explain how we optimized the load distribution across the CPUs and GPUs using the two-level adaptive method and describe the implementation in details. To overcome the low-bandwidth between the CPU and GPU communication, we present a software pipelining technique to hide the communication overhead. Combined with other traditional optimizations, the Linpack we developed achieved 196:7 GFLOPS on a single compute element of TianHe-1. This result is 70:1% of the peak compute capability, 3:3 times faster than the result by using the vendors library. On the full configuration of TianHe-1 our optimizations resulted in a Linpack performance of 0:563 PFLOPS, which made TianHe-1 the 5th fastest supercomputer on the Top500 list in November, 2009.

OpenMC: Towards Simplifying Programming for TianHe Supercomputers

Modern petascale and future exascale systems are massively heterogeneous architectures. Developing productive intra-node programming models is crucial toward addressing their programming challenge. We introduce a directive-based intra-node programming model, OpenMC, and show that this new model can achieve ease of programming, high performance, and the degree of portability desired for heterogeneous nodes, especially those in TianHe supercomputers. While existing models are geared towards offloading computations to accelerators (typically one), OpenMC aims to more uniformly and adequately exploit the potential offered by multiple CPUs and accelerators in a compute node. OpenMC achieves this by providing a unified abstraction of hardware resources as workers and facilitating the exploitation of asynchronous task parallelism on the workers. We present an overview of OpenMC, a prototyping implementation, and results from some initial comparisons with OpenMP and hand-written code in developing six applications on two types of nodes from TianHe supercomputers.

Toward the optimal configuration of dynamic voltage scaling points in real-time applications

In real-time applications, compiler-directed dynamic voltage scaling (DVS) could reduce energy consumption efficiently, where compiler put voltage scaling points in the proper places, and the supply voltage and clock frequency were adjusted to the relationship between the reduced time and the reduced workload. This paper presents the optimal configuration of dynamic voltage scaling points without voltage scaling overhead, which minimizes energy consumption. The conclusion is proved theoretically. Finally, it is confirmed by simulations with equally-spaced voltage scaling configuration.