Demo
Testing Code Insert
Last updated
Testing Code Insert
Last updated
package org.javaee7.el.standalone;
import org.jboss.arquillian.container.test.api.Deployment;
import org.jboss.arquillian.junit.Arquillian;
import org.jboss.shrinkwrap.api.Archive;
import org.jboss.shrinkwrap.api.ShrinkWrap;
import org.jboss.shrinkwrap.api.spec.JavaArchive;
import org.junit.Before;
import org.junit.Test;
import org.junit.runner.RunWith;
import javax.el.ELProcessor;
import static org.junit.Assert.assertEquals;
/**
* @author Alexis Hassler
*/
@RunWith(Arquillian.class)
public class ELResolverTest {
@Deployment
public static Archive<?> deploy() {
return ShrinkWrap.create(JavaArchive.class);
}
private ELProcessor elProcessor;
@Before
public void setup() {
elProcessor = new ELProcessor();
}
@Test
public void should_pick_in_the_array() {
Object result = elProcessor.eval("a = [1, 2, 3]; a[1]");
assertEquals(2L, result);
}
@Test
public void should_add() {
Object result = elProcessor.eval("((x,y) -> x+y)(4, 5)");
assertEquals(9L, result);
}
}
using ILGPU;
using ILGPU.Runtime;
using ILGPU.Runtime.CPU;
using ILGPU.Runtime.Cuda;
using ILGPU.Runtime.OpenCL;
using System.Diagnostics;
namespace Apex.CUDA
{
class Program
{
public static void Main(string[] args)
{
//BottleNeckTest();
PrintGpuDetails();
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}\n", "Length", "SingleThread", "TPL", "CLA", "CUDA");
//TestStart(10);
//TestStart(1_000);
//TestStart(10_000);
//TestStart(100_000);
//TestStart(1_000_000);
//TestStart(10_000_000);
//TestStart(100_000_000);
TestStart(1_000_000_000);
//TestStart(2_146_435_071);
Console.WriteLine("Done, Press any key to exit");
//Console.ReadKey();
}
public static void TestStart(long length)
{
var lengthString = length.ToString("#,##0");
Context con = Context.Create(builder => builder.AllAccelerators());
// Get a list of all available accelerators (including the CPU/GPU)
List<AcceleratorType> accTypes = new List<AcceleratorType>();
foreach (Device device in con)
{
accTypes.Add(device.AcceleratorType);
}
if (accTypes.Contains(AcceleratorType.OpenCL) && accTypes.Contains(AcceleratorType.Cuda))
{
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}", lengthString, SingleThread(length), Tpl(length), CLA(length), CUDA(length));
}
else if (accTypes.Contains(AcceleratorType.OpenCL))
{
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}", lengthString, SingleThread(length), Tpl(length), CLA(length), "N/A");
}
else if (accTypes.Contains(AcceleratorType.Cuda))
{
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}", lengthString, SingleThread(length), Tpl(length), "N/A", CUDA(length));
}
else
{
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}", lengthString, SingleThread(length), Tpl(length), "N/A", "N/A");
}
}
public static void PrintGpuDetails()
{
Context acceleratorContext = Context.Create(builder => builder.AllAccelerators());
foreach (var accelerator in acceleratorContext)
{
Console.WriteLine($"Name: {accelerator.Name}");
Console.WriteLine($"MemorySize: {accelerator.MemorySize}");
Console.WriteLine($"MaxThreadsPerGroup: {accelerator.MaxNumThreadsPerGroup}");
Console.WriteLine($"MaxSharedMemoryPerGroup: {accelerator.MaxSharedMemoryPerGroup}");
Console.WriteLine($"MaxGridSize: {accelerator.MaxGridSize}");
Console.WriteLine($"MaxConstantMemory: {accelerator.MaxConstantMemory}");
Console.WriteLine($"WarpSize: {accelerator.WarpSize}");
Console.WriteLine($"NumMultiprocessors: {accelerator.NumMultiprocessors}");
Console.WriteLine();
}
}
public static string CLA(long length)
{
String result = "";
Context context = Context.CreateDefault();
Accelerator acceleratorCLA = context.CreateCLAccelerator(0);
result = result + Gpu(acceleratorCLA, length);
acceleratorCLA.Dispose();
context.Dispose();
return result;
}
public static string CUDA(long length)
{
String result = "";
Context context = Context.CreateDefault();
Accelerator acceleratorCUDA = context.CreateCudaAccelerator(0);
result = result + Gpu(acceleratorCUDA, length);
acceleratorCUDA.Dispose();
context.Dispose();
return result;
}
public static string Gpu(Accelerator accelerator, long length)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
// Allocate memory on the accelerator.
var deviceOutput = accelerator.Allocate1D<double>(length);
// Load / Compile the kernel. This is where the magic happens.
var loadedKernel = accelerator.LoadAutoGroupedStreamKernel(
(Index1D i, ArrayView<double> output) =>
{
output[i] = 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429;
});
// Tell the accelerator to start computing the kernel
loadedKernel((int)deviceOutput.Length, deviceOutput.View);
// Wait for the accelerator to be finished with whatever it's doing
// in this case it just waits for the kernel to finish.
accelerator.Synchronize();
var result = deviceOutput.GetAsArray1D();
return stopwatch.ElapsedMilliseconds.ToString("#,##0");
}
public static string Tpl(long length)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
double[] output = new double[length];
Parallel.For(0, output.Length,
(long i) =>
{
output[i] = 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429;
});
return stopwatch.ElapsedMilliseconds.ToString("#,##0");
}
public static string SingleThread(long length)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
double[] output = new double[length];
for (int i = 0; i < output.Length; i++)
{
output[i] = 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429;
}
return stopwatch.ElapsedMilliseconds.ToString("#,##0");
}
}
}using ILGPU;
using ILGPU.Runtime;
using ILGPU.Runtime.CPU;
using ILGPU.Runtime.Cuda;
using ILGPU.Runtime.OpenCL;
using System.Diagnostics;
namespace Apex.CUDA
{
class Program
{
public static void Main(string[] args)
{
//BottleNeckTest();
PrintGpuDetails();
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}\n", "Length", "SingleThread", "TPL", "CLA", "CUDA");
//TestStart(10);
//TestStart(1_000);
//TestStart(10_000);
//TestStart(100_000);
//TestStart(1_000_000);
//TestStart(10_000_000);
//TestStart(100_000_000);
TestStart(1_000_000_000);
//TestStart(2_146_435_071);
Console.WriteLine("Done, Press any key to exit");
//Console.ReadKey();
}
public static void TestStart(long length)
{
var lengthString = length.ToString("#,##0");
Context con = Context.Create(builder => builder.AllAccelerators());
// Get a list of all available accelerators (including the CPU/GPU)
List<AcceleratorType> accTypes = new List<AcceleratorType>();
foreach (Device device in con)
{
accTypes.Add(device.AcceleratorType);
}
if (accTypes.Contains(AcceleratorType.OpenCL) && accTypes.Contains(AcceleratorType.Cuda))
{
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}", lengthString, SingleThread(length), Tpl(length), CLA(length), CUDA(length));
}
else if (accTypes.Contains(AcceleratorType.OpenCL))
{
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}", lengthString, SingleThread(length), Tpl(length), CLA(length), "N/A");
}
else if (accTypes.Contains(AcceleratorType.Cuda))
{
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}", lengthString, SingleThread(length), Tpl(length), "N/A", CUDA(length));
}
else
{
Console.WriteLine("{0,-20} {1,-20} {2,-20} {3,-20} {4,-20}", lengthString, SingleThread(length), Tpl(length), "N/A", "N/A");
}
}
public static void PrintGpuDetails()
{
Context acceleratorContext = Context.Create(builder => builder.AllAccelerators());
foreach (var accelerator in acceleratorContext)
{
Console.WriteLine($"Name: {accelerator.Name}");
Console.WriteLine($"MemorySize: {accelerator.MemorySize}");
Console.WriteLine($"MaxThreadsPerGroup: {accelerator.MaxNumThreadsPerGroup}");
Console.WriteLine($"MaxSharedMemoryPerGroup: {accelerator.MaxSharedMemoryPerGroup}");
Console.WriteLine($"MaxGridSize: {accelerator.MaxGridSize}");
Console.WriteLine($"MaxConstantMemory: {accelerator.MaxConstantMemory}");
Console.WriteLine($"WarpSize: {accelerator.WarpSize}");
Console.WriteLine($"NumMultiprocessors: {accelerator.NumMultiprocessors}");
Console.WriteLine();
}
}
public static string CLA(long length)
{
String result = "";
Context context = Context.CreateDefault();
Accelerator acceleratorCLA = context.CreateCLAccelerator(0);
result = result + Gpu(acceleratorCLA, length);
acceleratorCLA.Dispose();
context.Dispose();
return result;
}
public static string CUDA(long length)
{
String result = "";
Context context = Context.CreateDefault();
Accelerator acceleratorCUDA = context.CreateCudaAccelerator(0);
result = result + Gpu(acceleratorCUDA, length);
acceleratorCUDA.Dispose();
context.Dispose();
return result;
}
public static string Gpu(Accelerator accelerator, long length)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
// Allocate memory on the accelerator.
var deviceOutput = accelerator.Allocate1D<double>(length);
// Load / Compile the kernel. This is where the magic happens.
var loadedKernel = accelerator.LoadAutoGroupedStreamKernel(
(Index1D i, ArrayView<double> output) =>
{
output[i] = 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429;
});
// Tell the accelerator to start computing the kernel
loadedKernel((int)deviceOutput.Length, deviceOutput.View);
// Wait for the accelerator to be finished with whatever it's doing
// in this case it just waits for the kernel to finish.
accelerator.Synchronize();
var result = deviceOutput.GetAsArray1D();
return stopwatch.ElapsedMilliseconds.ToString("#,##0");
}
public static string Tpl(long length)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
double[] output = new double[length];
Parallel.For(0, output.Length,
(long i) =>
{
output[i] = 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429;
});
return stopwatch.ElapsedMilliseconds.ToString("#,##0");
}
public static string SingleThread(long length)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
double[] output = new double[length];
for (int i = 0; i < output.Length; i++)
{
output[i] = 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429 * 5.2429049278429;
}
return stopwatch.ElapsedMilliseconds.ToString("#,##0");
}
}
}