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Diffstat (limited to 'tensorflow/docs_src/performance/xla/index.md')
| -rw-r--r-- | tensorflow/docs_src/performance/xla/index.md | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/tensorflow/docs_src/performance/xla/index.md b/tensorflow/docs_src/performance/xla/index.md index 8f5de83ea6..770737c34c 100644 --- a/tensorflow/docs_src/performance/xla/index.md +++ b/tensorflow/docs_src/performance/xla/index.md @@ -14,7 +14,7 @@ XLA (Accelerated Linear Algebra) is a domain-specific compiler for linear algebra that optimizes TensorFlow computations. The results are improvements in speed, memory usage, and portability on server and mobile platforms. Initially, most users will not see large benefits from XLA, but are welcome to experiment -by using XLA via @{$jit$just-in-time (JIT) compilation} or @{$tfcompile$ahead-of-time (AOT) compilation}. Developers targeting new hardware accelerators are +by using XLA via [just-in-time (JIT) compilation](../../performance/xla/jit.md) or [ahead-of-time (AOT) compilation](../../performance/xla/tfcompile.md). Developers targeting new hardware accelerators are especially encouraged to try out XLA. The XLA framework is experimental and in active development. In particular, @@ -54,13 +54,13 @@ We had several objectives for XLA to work with TensorFlow: The input language to XLA is called "HLO IR", or just HLO (High Level Optimizer). The semantics of HLO are described on the -@{$operation_semantics$Operation Semantics} page. It +[Operation Semantics](../../performance/xla/operation_semantics.md) page. It is most convenient to think of HLO as a [compiler IR](https://en.wikipedia.org/wiki/Intermediate_representation). XLA takes graphs ("computations") defined in HLO and compiles them into machine instructions for various architectures. XLA is modular in the sense that it is -easy to slot in an alternative backend to @{$developing_new_backend$target some novel HW architecture}. The CPU backend for x64 and ARM64 as +easy to slot in an alternative backend to [target some novel HW architecture](../../performance/xla/developing_new_backend.md). The CPU backend for x64 and ARM64 as well as the NVIDIA GPU backend are in the TensorFlow source tree. The following diagram shows the compilation process in XLA: @@ -94,5 +94,5 @@ CPU backend supports multiple CPU ISAs. ## Supported Platforms -XLA currently supports @{$jit$JIT compilation} on x86-64 and NVIDIA GPUs; and -@{$tfcompile$AOT compilation} for x86-64 and ARM. +XLA currently supports [JIT compilation](../../performance/xla/jit.md) on x86-64 and NVIDIA GPUs; and +[AOT compilation](../../performance/xla/tfcompile.md) for x86-64 and ARM. |