Pinned Repositories
-hello-world
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Ares
Ares is a high performance and fault tolerant distributed stream processing system, which considers both both system performance and fault tolerant capability during task allocation and use a game-theoretic approach to obtain an optimal scheduler for task allocation. Ares greatly outperforms Storm in terms of system throughput and the average processing latency.
Argus
Argus is a novel RDMA-assisted job scheduler which achieves high resource utilization by fully exploiting the structure feature of stage dependency. Comprehensive experiments using large-scale traces collected from real world show that Argus reduces job completion time and job makespan by 21% and 20%, respectively, compared to RDMA-Spark.
awesome-DeepLearning
深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI
LDCF
LDCF is a novel efficient approximate set representation structure for large-scale dynamic data sets. LDCF uses a novel multi-level tree structure and reduces the worst insertion and membership testing times from O(N) to O(1).
PStream
PStream is a popularity-aware differentiated distributed stream processing system, which identifies the popularity of keys in the stream data and uses a differentiated partitioning scheme. PStream greatly outperforms Storm on skew distributed data in terms of throughput and processing latency.
Simois
Simois is a scalable distributed stream join system, which supports efficient join operations in two streams with highly skewed data distribution. Simois can support the completeness of the join results, and greatly outperforms the existing stream join systems in terms of system throughput and the average processing latency.
gpt_academic
为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。
Safety-Prompts
Chinese safety prompts for evaluating and improving the safety of LLMs. 中文安全prompts，用于评估和提升大模型的安全性。
Argus
Argus is a novel RDMA-assisted job scheduler which achieves high resource utilization by fully exploiting the structure feature of stage dependency. Comprehensive experiments using large-scale traces collected from real world show that Argus reduces job completion time and job makespan by 21% and 20%, respectively, compared to RDMA-Spark.
wusi1590's Repositories
wusi1590/awesome-DeepLearning
深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI
wusi1590/Argus
Argus is a novel RDMA-assisted job scheduler which achieves high resource utilization by fully exploiting the structure feature of stage dependency. Comprehensive experiments using large-scale traces collected from real world show that Argus reduces job completion time and job makespan by 21% and 20%, respectively, compared to RDMA-Spark.
wusi1590/LDCF
LDCF is a novel efficient approximate set representation structure for large-scale dynamic data sets. LDCF uses a novel multi-level tree structure and reduces the worst insertion and membership testing times from O(N) to O(1).
wusi1590/Ares
Ares is a high performance and fault tolerant distributed stream processing system, which considers both both system performance and fault tolerant capability during task allocation and use a game-theoretic approach to obtain an optimal scheduler for task allocation. Ares greatly outperforms Storm in terms of system throughput and the average processing latency.
wusi1590/PStream
PStream is a popularity-aware differentiated distributed stream processing system, which identifies the popularity of keys in the stream data and uses a differentiated partitioning scheme. PStream greatly outperforms Storm on skew distributed data in terms of throughput and processing latency.
wusi1590/Simois
Simois is a scalable distributed stream join system, which supports efficient join operations in two streams with highly skewed data distribution. Simois can support the completeness of the join results, and greatly outperforms the existing stream join systems in terms of system throughput and the average processing latency.
wusi1590/-hello-world
Just another repository