Bench 2020 Call for Papers

 In News

Benchmarking, measuring, and optimizing are fundamental human activities. The organizing committee is pleased to invite you to take part in Bench’20 to be held in Atlanta, Georgia, USA. This symposium (Bench’20) is organized by the International Open Benchmarking Council (BenchCouncil). Bench’20 overlaps with SC 20 (same place and same time), but it is NOT affiliated with the SC conference. The main themes of Bench’20 are benchmarking, measuring, and optimizing systems and applications in the areas of big data, AI, block chain, HPC, datacenters, IoT, and edge computing.

The Bench conference has three defining characteristics. First, it provides a high-quality, single-track forum for presenting results and discussing ideas that further the knowledge and understanding of the benchmark community as a whole. Second, it is a multi-disciplinary conference. The past conferences attracted the researchers and practitioners from the architecture, systems, algorithms, and applications communities. Third, it includes both invited sessions and contributed sessions.

Regularly, Bench’20 will present the BenchCouncil Achievement Award ($3000), the BenchCouncil Rising Star Award ($1000), and the BenchCouncil Best Paper Award ($1000).

As its duty, BenchCouncil incubates and hosts benchmark projects, and further encourages reliable and reproducible research using the benchmarks from BenchCouncil or other organizations. To this end, we present the BenchCouncil Award for Excellence for Reproducible Research to the papers using all publicly available benchmarks. Each winning paper earns a $100 prize, maximally up to 12 papers: 4 papers for each category of poster, spotlight, and oral.

Call for papers

Specific topics of interest include, but are not limited to, the following.

**Synthetics or real-world data sets of:

**Benchmark, measurement, and optimization of:

**Benchmark specifications and open-source implementation reports of:

** Methodologies, abstractions, metrics, algorithms, and tools in benchmarking, measurement, and optimization for:

** Benchmark-driven domain-specific co-design of:

** Test methodologies and systems of:

** Workload characterization of:

-Big data



-Machine learning

-Big scientific data



-Warehouse-scale computing

-Mobile robotics

-Edge and fog computing


-Block chain

-Data management and storage

-Medicine, finance and education


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