Renderscript offers a high performance computation API at the native level that you write in C (C99 standard). Renderscript gives your apps the ability to run operations with automatic parallelization across all available processor cores. It also supports different types of processors such as the CPU, GPU or DSP. Renderscript is useful for apps that do image processing, mathematical modeling, or any operations that require lots of mathematical computation.
In addition, you have access to all of these features without having to write code to support different architectures or a different amount of processing cores. You also do not need to recompile your application for different processor types, because Renderscript code is compiled on the device at runtime.
Deprecation Notice: Earlier versions of Renderscript included
an experimental graphics engine component. This component
is now deprecated as of Android 4.1 (most of the APIs in rs_graphics.rsh
and the corresponding APIs in {@link android.renderscript}).
If you have apps that render graphics with Renderscript, we highly
recommend you convert your code to another Android graphics rendering option.
The Renderscript runtime operates at the native level and still needs to communicate with the Android VM, so the way a Renderscript application is set up is different from a pure VM application. An application that uses Renderscript is still a traditional Android application that runs in the VM, but you write Renderscript code for the parts of your program that require it. No matter what you use it for, Renderscript remains platform independent, so you do not have to target multiple architectures (for example, ARM v5, ARM v7, x86).
The Renderscript system adopts a control and slave architecture where the low-level Renderscript runtime code is controlled by the higher level Android system that runs in a virtual machine (VM). The Android VM still retains all control of memory management and binds memory that it allocates to the Renderscript runtime, so the Renderscript code can access it. The Android framework makes asynchronous calls to Renderscript, and the calls are placed in a message queue and processed as soon as possible. Figure 1 shows how the Renderscript system is structured.
Figure 1. Renderscript system overview
When using Renderscript, there are three layers of APIs that enable communication between the Renderscript runtime and Android framework code:
Because of the way Renderscript is structured, the main advantages are:
The main disadvantages are:
For a more detailed explanation of how all of these layers work together, see Advanced Renderscript.
Renderscripts scale to the amount of
processing cores available on the device. This is enabled through a function named
rsForEach() (or the forEach_root() method at the Android framework level).
that automatically partitions work across available processing cores on the device.
For now, Renderscript can only take advantage of CPU
cores, but in the future, they can potentially run on other types of processors such as GPUs and
DSPs.
Implementing a Renderscript involves creating a .rs file that contains
your Renderscript code and calling it at the Android framework level with the
forEach_root() or at the Renderscript runtime level with the
rsForEach() function. The following diagram describes how a typical
Renderscript is set up:
Figure 1. Renderscript overview
The following sections describe how to create a simple Renderscript and use it in an Android application. This example uses the HelloCompute Renderscript sample that is provided in the SDK as a guide (some code has been modified from its original form for simplicity).
Your Renderscript code resides in .rs and .rsh files in the
<project_root>/src/ directory. This code contains the computation logic
and declares all necessary variables and pointers.
Every .rs file generally contains the following items:
#pragma rs java_package_name(package.name))
that declares the package name of the .java reflection of this Renderscript.#pragma version(1)) that declares the version of
Renderscript that you are using (1 is the only value for now).A root() function that is the main worker function. The root function is
called by the rsForEach function, which allows the Renderscript code to be called and
executed on multiple cores if they are available. The root() function must return
void and accept the following arguments:
The following arguments are optional, but both must be supplied if you choose to use them:
init() function. This allows you to do any initialization
before the root() function runs, such as initializing variables. This
function runs once and is called automatically when the Renderscript starts, before anything
else in your Renderscript..rsh files if desired)The following code shows how the mono.rs file is implemented:
#pragma version(1)
#pragma rs java_package_name(com.example.android.rs.hellocompute)
//multipliers to convert a RGB colors to black and white
const static float3 gMonoMult = {0.299f, 0.587f, 0.114f};
void root(const uchar4 *v_in, uchar4 *v_out) {
//unpack a color to a float4
float4 f4 = rsUnpackColor8888(*v_in);
//take the dot product of the color and the multiplier
float3 mono = dot(f4.rgb, gMonoMult);
//repack the float to a color
*v_out = rsPackColorTo8888(mono);
}
You can call the Renderscript from your Android framework code by
creating a Renderscript object by instantiating the (ScriptC_script_name)
class. This class contains a method, forEach_root(), that lets you invoke
rsForEach. You give it the same parameters that you would if you were invoking it
at the Renderscript runtime level. This technique allows your Android application to offload
intensive mathematical calculations to Renderscript. See the HelloCompute sample to see
how a simple Android application can utilize Renderscript.
To call Renderscript at the Android framework level:
ScriptC_script_name class.forEach_root(), passing in the allocations, the
Renderscript, and any optional user-defined data. The output allocation will contain the output
of the Renderscript.The following example, taken from the HelloCompute sample, processes
a bitmap and outputs a black and white version of it. The
createScript() method carries out the steps described previously. This method calls the
Renderscript, mono.rs, passing in memory allocations that store the bitmap to be processed
as well as the eventual output bitmap. It then displays the processed bitmap onto the screen:
package com.example.android.rs.hellocompute;
import android.app.Activity;
import android.os.Bundle;
import android.graphics.BitmapFactory;
import android.graphics.Bitmap;
import android.renderscript.RenderScript;
import android.renderscript.Allocation;
import android.widget.ImageView;
public class HelloCompute extends Activity {
private Bitmap mBitmapIn;
private Bitmap mBitmapOut;
private RenderScript mRS;
private Allocation mInAllocation;
private Allocation mOutAllocation;
private ScriptC_mono mScript;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.main);
mBitmapIn = loadBitmap(R.drawable.data);
mBitmapOut = Bitmap.createBitmap(mBitmapIn.getWidth(), mBitmapIn.getHeight(),
mBitmapIn.getConfig());
ImageView in = (ImageView) findViewById(R.id.displayin);
in.setImageBitmap(mBitmapIn);
ImageView out = (ImageView) findViewById(R.id.displayout);
out.setImageBitmap(mBitmapOut);
createScript();
}
private void createScript() {
mRS = RenderScript.create(this);
mInAllocation = Allocation.createFromBitmap(mRS, mBitmapIn,
Allocation.MipmapControl.MIPMAP_NONE,
Allocation.USAGE_SCRIPT);
mOutAllocation = Allocation.createTyped(mRS, mInAllocation.getType());
mScript = new ScriptC_mono(mRS, getResources(), R.raw.mono);
mScript.forEach_root(mInAllocation, mOutAllocation);
mOutAllocation.copyTo(mBitmapOut);
}
private Bitmap loadBitmap(int resource) {
final BitmapFactory.Options options = new BitmapFactory.Options();
options.inPreferredConfig = Bitmap.Config.ARGB_8888;
return BitmapFactory.decodeResource(getResources(), resource, options);
}
}
To call Renderscript from another Renderscript file:
rsForEach(), passing in the allocations and any optional user-defined data.
The output allocation will contain the output of the Renderscript.rs_script script; rs_allocation in_allocation; rs_allocation out_allocation; UserData_t data; ... rsForEach(script, in_allocation, out_allocation, &data, sizeof(data));
In this example, assume that the script and memory allocations have already been
allocated and bound at the Android framework level and that UserData_t is a struct
declared previously. Passing a pointer to a struct and the size of the struct to rsForEach
is optional, but useful if your Renderscript requires additional information other than
the necessary memory allocations.
You can define the floating point precision required by your compute algorithms. This is useful if you require less precision than the IEEE 754-2008 standard (used by default). You can define the floating-point precision level of your script with the following pragmas:
#pragma rs_fp_full (default if nothing is specified): For apps that
require floating point precision as outlined by the IEEE 754-2008 standard.
#pragma rs_fp_relaxed - For apps that don’t require
strict IEEE 754-2008 compliance and can tolerate less precision. This mode enables
flush-to-zero for denorms and round-towards-zero.
#pragma rs_fp_imprecise - For apps that don’t have stringent precision requirements. This mode enables
everything in rs_fp_relaxed along with the following: