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# Release 1.5.0
## Breaking Changes
-* Prebuilt binaries are now built against CUDA 9 and cuDNN 7.
+* Prebuilt binaries are now built against CUDA 9.0 and cuDNN 7.
+* Our Linux binaries are built using ubuntu 16 containers, potentially
+ introducing glibc incompatibility issues with ubuntu 14.
* Starting from 1.6 release, our prebuilt binaries will use AVX instructions.
This may break TF on older CPUs.
+## Known Bugs
+* Using XLA:GPU with CUDA 9 and CUDA 9.1 results in garbage results and/or
+ `CUDA_ILLEGAL_ADDRESS` failures.
+
+ Google discovered in mid-December 2017 that the PTX-to-SASS compiler in CUDA 9
+ and CUDA 9.1 sometimes does not properly compute the carry bit when
+ decomposing 64-bit address calculations with large offsets (e.g. `load [x +
+ large_constant]`) into 32-bit arithmetic in SASS.
+
+ As a result, these versions of `ptxas` miscompile most XLA programs which use
+ more than 4GB of temp memory. This results in garbage results and/or
+ `CUDA_ERROR_ILLEGAL_ADDRESS` failures.
+
+ A fix in CUDA 9.1.121 is expected in late February 2018. We do not expect a
+ fix for CUDA 9.0.x. Until the fix is available, the only workaround is to
+ [downgrade](https://developer.nvidia.com/cuda-toolkit-archive) to CUDA 8.0.x
+ or disable XLA:GPU.
+
+ TensorFlow will print a warning if you use XLA:GPU with a known-bad version of
+ CUDA; see e00ba24c4038e7644da417ddc639169b6ea59122.
+
## Major Features And Improvements
* [Eager execution](https://github.com/tensorflow/tensorflow/tree/r1.5/tensorflow/contrib/eager)
preview version is now available.
* [TensorFlow Lite](https://github.com/tensorflow/tensorflow/tree/r1.5/tensorflow/contrib/lite)
dev preview is now available.
-* CUDA 9 and cuDNN 7 support.
+* CUDA 9.0 and cuDNN 7 support.
* Accelerated Linear Algebra (XLA):
* Add `complex64` support to XLA compiler.
* `bfloat` support is now added to XLA infrastructure.