Dhrystone: a synthetic systems programming benchmark
Communications of the ACM
Runtime Power Monitoring in High-End Processors: Methodology and Empirical Data
Proceedings of the 36th annual IEEE/ACM International Symposium on Microarchitecture
Improved automatic testcase synthesis for performance model validation
Proceedings of the 19th annual international conference on Supercomputing
JouleSort: a balanced energy-efficiency benchmark
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Distilling the essence of proprietary workloads into miniature benchmarks
ACM Transactions on Architecture and Code Optimization (TACO)
The PARSEC benchmark suite: characterization and architectural implications
Proceedings of the 17th international conference on Parallel architectures and compilation techniques
Energy-efficient cluster computing with FAWN: workloads and implications
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
Microprocessor power estimation using profile-driven program synthesis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Towards efficient supercomputing: searching for the right efficiency metric
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
Systematic Energy Characterization of CMP/SMT Processor Systems via Automated Micro-Benchmarks
MICRO-45 Proceedings of the 2012 45th Annual IEEE/ACM International Symposium on Microarchitecture
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Energy efficiency is a key design concern in contemporary processor and system design, in the embedded domain as well as in the enterprise domain. The focus on energy efficiency has led to a number of power benchmarking methods recently. For example, EEMBC released EnergyBench and SPEC released SPECpower to quantify a system's energy efficiency; also academics have proposed power benchmarks, such as JouleSort. A major limitation for each of these proposals is that they are tied to a specific benchmark, and hence, they provide limited insight with respect to why one system may be more energy-efficient than another. This paper proposes SWEEP, Synthetic Workloads for Energy Efficiency and Performance evaluation, a framework for generating synthetic workloads with specific behavioral characteristics. We employ SWEEP to generate a wide range of synthetic workloads while varying the instruction mix, ILP, memory access patterns, and I/O-intensiveness; and we use SWEEP to evaluate the energy efficiency of commercial computer systems across the workload space and learn about how the energy efficiency of a computer system is tied to its workload's characteristics. This paper also presents the Energy-Delay Diagram (EDD), a novel method for visualizing energy efficiency. The EDD clearly illustrates the energy versus performance trade-off, and provides more intuitive insight than the traditionally used EDP and ED2P metrics.