Gardner, P. P. et al. A meta-analysis of bioinformatics software benchmarks reveals that publication-bias unduly influences software accuracy.
It consists of a chain of data and compute intensive tasks that can be treated as good examples of software benchmarks for modern parallel hardware architectures.
The TI-82 runs at about 5.2Mhz, and software benchmarks show the TI-85 and TI-86 at about 4.5Mhz (but this may be slowed down due to display memory access).
The original TI-92 and early TI-89s are specified as 10Mhz but software benchmarks look closer to 9.4Mhz, perhaps because of display memory access slowing down the processor.
Consequently, software benchmarks and performance testing are still the best techniques to compare the effciency of emerging parallel architectures with the built-in support for parallelism at different levels.
The paper provides results for software benchmarks partitioned using the method and formal implementations of previous alternatives to demonstrate both the practical tractability of the linear programming approach and the increase in program acceleration potential deliverable.
In this paper we provide formal assignment results for software benchmarks partitioned using the WOA and previous execution paradigms for distributed heterogeneous architectures along with bounds and complexity information to demonstrate the robust performance improvements possible with the WOA.
As an experiment, we utilized a mobile application that runs software benchmarks coded in Java and C. We exercised the benchmarks in different execution scopes within the handheld target and a remote server counterpart, measuring the amount of energy required to complete each job.
Starting from some raw files of this dataset, we also provide here some processed data obtained through various bioinformatics tools (including Max Quant Skyline, MFPaQ, IRMa-hEIDI and Scaffold) in different workflows, to exemplify the use of such data in the context of software benchmarking, as discussed in details in the accompanying manuscript [1].
Numerical and implementation issues, optimization software, benchmarking, and case studies.
