Open deep learning compiler stack for cpu, gpu and specialized accelerators
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Aditya Atluri fa232720d0 changed makefile to build rocm backend (#355) 2017-08-19 17:05:38 -07:00
HalideIR@f3eb854595 [DOC] Release note (#340) 2017-08-17 11:42:14 -07:00
apps [FIX] Pass the attributes of master node (#304) 2017-08-09 08:32:37 -07:00
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include/tvm [PASS] RewriteUnsafeSelect lowers unsafe select to condition expr (#335) 2017-08-15 22:32:43 -07:00
jvm [tvm4j] disable proxy test for now (#307) 2017-08-10 09:36:22 -07:00
make [Contrib] CuDNN v7 Support (#311) 2017-08-15 12:37:10 -07:00
python [PASS] RewriteUnsafeSelect lowers unsafe select to condition expr (#335) 2017-08-15 22:32:43 -07:00
src [PASS] RewriteUnsafeSelect lowers unsafe select to condition expr (#335) 2017-08-15 22:32:43 -07:00
tests [PASS] RewriteUnsafeSelect lowers unsafe select to condition expr (#335) 2017-08-15 22:32:43 -07:00
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CMakeLists.txt Fix CUDA library search (#339) 2017-08-17 09:06:42 -07:00
CONTRIBUTORS.md [TUTORIAL] Optimize gemm on CPU add! (#270) 2017-07-25 22:58:41 -07:00
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README.md

TVM: Tensor IR Stack for Deep Learning Systems

GitHub license Build Status

Installation | Documentation | Tutorials | Operator Inventory | FAQ | Contributors | Release Notes

TVM is a Tensor intermediate representation(IR) stack for deep learning systems. It is designed to close the gap between the productivity-focused deep learning frameworks, and the performance- and efficiency-focused hardware backends. TVM works with deep learning frameworks to provide end to end compilation to different backends. Checkout our announcement for more details.

License

© Contributors, 2017. Licensed under an Apache-2.0 license.

Contribute to TVM

TVM adopts apache committer model, we aim to create an open source project that is maintained and owned by the community.