419 citations · 920 across the 71 of their papers we have counts for
71 papers
A Linear Combination-based Method to Construct Proxy Benchmarks for Big Data Workloads
Yikang Yang, Lei Wang, Jianfeng Zhan
During early stages of CPU design, benchmarks can only run on simulators to evaluate CPU performance. However, most big data benchmarks are too huge at code size scale, which cause…
AGIBench: A Multi-granularity, Multimodal, Human-referenced, Auto-scoring Benchmark for Large Language Models
Fei Tang, Wanling Gao, Luzhou Peng +1
Large language models (LLMs) like ChatGPT have revealed amazing intelligence. How to evaluate the question-solving abilities of LLMs and their degrees of intelligence is a hot-spot…
Does AI for science need another ImageNet Or totally different benchmarks? A case study of machine learning force fields
Yatao Li, Wanling Gao, Lei Wang +3
AI for science (AI4S) is an emerging research field that aims to enhance the accuracy and speed of scientific computing tasks using machine learning methods. Traditional AI benchma…
IterLara: A Turing Complete Algebra for Big Data, AI, Scientific Computing, and Database
Hongxiao Li, Wanling Gao, Lei Wang +1
\textsc{Lara} is a key-value algebra that aims at unifying linear and relational algebra with three types of operation abstraction. The study of \textsc{Lara}'s expressive ability…
DCNetBench: Scaleable Data Center Network Benchmarking
Ke Liu, Wanling Gao, Chunjie Luo +7
Data center networking is the central infrastructure of the modern information society. However, benchmarking them is very challenging as the real-world network traffic is difficul…
NHtapDB: Native HTAP Databases
Guoxin Kang, Lei Wang, Simin Chen +1
Native database (1) provides a near-data machine learning framework to facilitate generating real-time business insight, and predefined change thresholds will trigger online traini…