{ "graph_parallel_option": { "auto": true } } 参数解释如下: auto:配置为true表示全自动切分,配置为false表示半自动切分。 opt_level:指Tensor Parallel求解算法,支持配置为O2和O1,O2使用的是ILP算法,O1使用的是DP算法,若不配置,默认使用O2。 tensor_parallel_option:配置该
Chevalier, C., Pellegrini, F.: Pt-scotch: A tool for efficient parallel graph ordering. Parallel Comput. 34(6-8), 318–331 (2008) MathSciNetChevalier, C. and Pellegrini, F. 2008. PT-Scotch: A tool for efficient parallel graph ordering. Parallel Comput. 34, 318-331....
Graph-based LLM power tool for exploring many completions in parallel. Announcement·Try Online·Report a Bug About Flux is a power tool for interacting with large language models (LLMs) thatgenerates multiple completions per prompt in a tree structure and lets you explore the best ones in paral...
Consequently, if the tasks are executed in parallel, task j will have to wait for task i to send data. This is called data dependency , and the graph is a data-flow graph. However, if the channels represent completion signals, this depicts control dependency ; in that case, the graph ...
In view of the low computational efficiency and the limitations of the platform of the unsharp masking image enhancement algorithm, an unsharp masking image enhancement parallel algorithm based on Open Computing Language (OpenCL) is proposed. Based on th
Calls made by other processes targeting this process: task_for_pid: 0 thread_create: 0 thread_set_state: 0 Calls made by this process: task_for_pid: 0 thread_create: 0 thread_set_state: 0 Calls made by all processes on this machine: task_for_pid: 75659 thread_create: 0 thread_set...
In order to calculate GTOMm for a given value m, we need to multiply the matrices in the GPU to obtain A2,A3,A4,…,Am. We compute each of the Ai for all i={1,2,…,m}. Our algorithm computes Ai by multiplying A and Ai-1, thus requiring m calls to the cublasSgemm() function...
--enable_graph_parallel 功能说明 是否对原始大模型进行自动切分。 关联参数 --distributed_cluster_build参数开启大模型分布式编译后,才支持开启自动切分功能,原始大模型会按照--graph_parallel_option_path文件中的要求进行自动切分。 算法切分场景--cluster_config必
Runtime evaluation data of a parallel dependency graph may be collected, including the start time and stop time for each node in the graph. The visualization tool may process the data to generate performance visualizations as well as other analysis features. Performance visualizations may illustrate ...
In this study, we propose a parallel data mining system for analyzing big graph data generated on a bulk synchronous parallel (BSP) computing model and MapReduce computing model named mixed parallel graph mining (MPGM). This system has four sets of parallel graph mining algorithms programmed in...