hummingbird
/
graphengine
Not watched
2
0
Fork 0
Code
Releases 13 Wiki Activity
Issues 0 Pull Requests 0 Datasets Model Cloudbrain
You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.
2640 Commits
28 Branches
21 MB
0 Download
 
 
 
 
 
 
Tree: 3f648013e5
Branches Tags
${ item.name }
Create branch ${ searchTerm }
from '3f648013e5'
${ noResults }
graphengine/ge
mindspore-ci-bot 3f648013e5 !1728 fix sc 3 years ago
..
analyzer ge log optimize 3 years ago
client !1676 GE支持将混合精度黑白灰名单配置参数modify_mixlist传递给FE 3 years ago
common remove 3 years ago
engine_manager Move host_cpu kernel to cann. 3 years ago
executor !1673 Move host_cpu kernel to cann. 3 years ago
ge_local_engine Move host_cpu kernel to cann. 3 years ago
ge_runtime fix 3 years ago
generator fix sc 3 years ago
graph !1728 fix sc 3 years ago
host_kernels fix format 3 years ago
hybrid !1728 fix sc 3 years ago
inc update code from yellow zone 20201013 4 years ago
init Support session scope memory 3 years ago
ir_build fix format 3 years ago
model run_graph_with_stream. 3 years ago
offline add complex64 support, add data_type support and fix release error in aclgrphGenerateForOp 3 years ago
opskernel_manager Change optimizer name. 3 years ago
plugin/engine fixed compile issue 3 years ago
proto change op_mapping and dump_task namespace. 3 years ago
session add modify_mixlist parameter. 3 years ago
single_op support memcpy in singleop 3 years ago
stub python3,7 modify python3 3 years ago
CMakeLists.txt !1673 Move host_cpu kernel to cann. 3 years ago
README.md update cmake 4 years ago
ge_inference.mk !1564 Bugfix: Delete abandoned optimize pass 3 years ago
ge_runner.mk !1564 Bugfix: Delete abandoned optimize pass 3 years ago
module.mk update ge folder 4 years ago

README.md

Delete task

Are you sure you want to delete this task? Once this task is deleted, it cannot be recovered.

cancel
confirm

图引擎模块(GE)是MindSpore的一个子模块，其代码由C++实现，位于前端模块ME和底层硬件之间，起到承接作用。图引擎模块以ME下发的图作为输入，然后进行一系列的深度图优化操作，最后输出一张可以在底层硬件上高效运行的图。GE针对昇腾AI处理器的硬件结构特点，做了特定的优化工作，以此来充分发挥出昇腾AI处理器的强大算力。在进行模型训练/推理时，GE会被自动调用而用户并不感知。GE主要由GE API和GE Core两部分组成，详细的架构图如下所示

C++ Text Makefile Shell CMake other