The tradeoffs of fused memory hierarchies in heterogeneous computing architectures
Proceedings of the 9th conference on Computing Frontiers
Power and performance analysis of GPU-accelerated systems
HotPower'12 Proceedings of the 2012 USENIX conference on Power-Aware Computing and Systems
Power efficiency evaluation of block ciphers on GPU-integrated multicore processor
ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Inter-warp instruction temporal locality in deep-multithreaded GPUs
ARCS'13 Proceedings of the 26th international conference on Architecture of Computing Systems
GPUWattch: enabling energy optimizations in GPGPUs
Proceedings of the 40th Annual International Symposium on Computer Architecture
Evaluating integrated graphics processors for data center workloads
Proceedings of the Workshop on Power-Aware Computing and Systems
Easy, fast, and energy-efficient object detection on heterogeneous on-chip architectures
ACM Transactions on Architecture and Code Optimization (TACO)
Power Modeling for Heterogeneous Processors
Proceedings of Workshop on General Purpose Processing Using GPUs
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We present a comprehensive study on the performance and power consumption of a recent ATI GPU. By employing a rigorous statistical model to analyze execution behaviors of representative general-purpose GPU (GPGPU) applications, we conduct insightful investigations on the target GPU architecture. Our results demonstrate that the GPU execution throughput and the power dissipation are dependent on different architectural variables. Furthermore, we design a set of micro-benchmarks to study the power consumption features of different function units on the GPU. Based on those results, we derive instructive principles that can guide the design of power-efficient high performance computing systems.