Add CPU/AVX page

cpu.md

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+---
+title: CPU and AVX
+short_title: CPU
+description: CPU and AVX support in ND4J/Deeplearning4j
+layout: default
+redirect_from: "/cpu"
+---
+
+# ND4J - CPU (nd4j-native) AVX Configuration
+
+### What is AVX, and why does it matter?
+
+AVX (Advanced Vector Extensions) is a set of CPU instructions for accelerating numerical computations. See [Wikipedia](https://en.wikipedia.org/wiki/Advanced_Vector_Extensions) for more details.
+
+Note that AVX only applies to nd4j-native (CPU) backend for x86 devices, not GPUs and not ARM/PPC devices.
+
+Why AVX matters: performance. You want to use the version of ND4J compiled with the highest level of AVX supported by your system.
+
+
+AVX support for different CPUs - summary:
+* Most modern x86 CPUs: AVX2 is supported
+* Some high-end server CPUs: AVX512 may be supported 
+* Old CPUs (pre 2012) and low power x86 (Atom, Celeron): No AVX support (usually) 
+
+AVX is backward compatible, so for example it's possible run a generic x86 or AVX2 binary on a system supporting AVX512.
+However it is not possible to run 
+
+Note on current snapshots (and in future releases, after 1.0.0-beta5) you may get a warning as follows, if AVX is not configured optimally:
+```
+o.n.l.c.n.CpuNDArrayFactory - *********************************** CPU Feature Check Warning ***********************************
+o.n.l.c.n.CpuNDArrayFactory - Warning: Initializing ND4J with Generic x86 binary on a CPU with AVX/AVX2 support
+o.n.l.c.n.CpuNDArrayFactory - Using ND4J with AVX/AVX2 will improve performance. See deeplearning4j.org/cpu for more details
+o.n.l.c.n.CpuNDArrayFactory - Or set environment variable ND4J_IGNORE_AVX=true to suppress this warning
+o.n.l.c.n.CpuNDArrayFactory - ************************************************************************************************
+```
+
+
+### Configuring AVX in ND4J/DL4J
+
+As noted earlier, for best performance you should use the version of ND4J that matches your CPU's supported AVX level. 
+
+ND4J defaults configuration (when just including the nd4j-native or nd4j-native-platform dependencies without maven classifier configuration):
+* 1.0.0-beta5 and earlier: "generic x86" (no AVX) is the default for nd4j/nd4j-platform dependencies
+* Current snapshots and later versions of ND4J: AVX2 is the default
+
+
+To configure AVX2 and AVX512, you need to specify a classifier for the appropriate architecture.
+
+The following binaries (nd4j-native classifiers) are provided for x86 architectures:
+* Generic x86 (no AVX): `linux-x86_64`, `windows-x86_64`, `macosx-x86_64` 
+* AVX2: `linux-x86_64-avx2`, `windows-x86_64-avx2`, `macosx-x86_64-avx2`
+* AVX512: `linux-x86_64-avx512`
+
+
+**Example: Configuring AVX2 on Windows (Maven pom.xml)**
+```
+<dependency>
+    <groupId>org.nd4j</groupId>
+    <artifactId>nd4j-native</artifactId>
+    <version>${nd4j.version}</version>
+</dependency>
+
+<dependency>
+    <groupId>org.nd4j</groupId>
+    <artifactId>nd4j-native</artifactId>
+    <version>${nd4j.version}</version>
+    <classifier>windows-x86_64-avx2</classifier>
+</dependency>
+```
+
+
+**Example: Configuring AVX512 on Linux (Maven pom.xml)**
+```
+<dependency>
+    <groupId>org.nd4j</groupId>
+    <artifactId>nd4j-native</artifactId>
+    <version>${nd4j.version}</version>
+</dependency>
+
+<dependency>
+    <groupId>org.nd4j</groupId>
+    <artifactId>nd4j-native</artifactId>
+    <version>${nd4j.version}</version>
+    <classifier>linux-x86_64-avx512</classifier>
+</dependency>
+```
+
+Note that you need *both* nd4j-native dependencies - with and without the classifier.