NoAvailableBackendException: Please ensure that you have an nd4j backend on your classpath

NoAvailableBackendException

Exception in thread "main" java.lang.ExceptionInInitializerError
	at org.deeplearning4j.nn.conf.NeuralNetConfiguration$Builder.seed(NeuralNetConfiguration.java:671)
	at Trainer.TrainerImpl.main(TrainerImpl.java:54)
Caused by: java.lang.RuntimeException: org.nd4j.linalg.factory.Nd4jBackend$NoAvailableBackendException: Please ensure that you have an nd4j backend on your classpath. Please see: http://nd4j.org/getstarted.html
	at org.nd4j.linalg.factory.Nd4j.initContext(Nd4j.java:5768)
	at org.nd4j.linalg.factory.Nd4j.<clinit>(Nd4j.java:202)
	... 2 more
Caused by: org.nd4j.linalg.factory.Nd4jBackend$NoAvailableBackendException: Please ensure that you have an nd4j backend on your classpath. Please see: http://nd4j.org/getstarted.html
	at org.nd4j.linalg.factory.Nd4jBackend.load(Nd4jBackend.java:213)
	at org.nd4j.linalg.factory.Nd4j.initContext(Nd4j.java:5765)
	... 3 more

pom.xml

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
	xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
	<modelVersion>4.0.0</modelVersion>
	<properties>
		<maven.compiler.source>1.8</maven.compiler.source>
		<maven.compiler.target>1.8</maven.compiler.target>
		<slf4j.version>1.7.21</slf4j.version>
		<spark.version>2.1.0</spark.version>
		<guava.version>23.0</guava.version>
		<jfreechart.version>1.0.19</jfreechart.version>
	</properties>

	<parent>
		<groupId>Crypto</groupId>
		<artifactId>Trader</artifactId>
		<version>0.0.1-SNAPSHOT</version>
	</parent>

	<artifactId>primary-source</artifactId>
	<packaging>jar</packaging>

	<name>core project classes</name>

	<repositories>
		<repository>
			<id>jitpack.io</id>
			<url>https://jitpack.io</url>
		</repository>
	</repositories>

	<dependencies>
		<dependency>
			<groupId>org.deeplearning4j</groupId>
			<artifactId>deeplearning4j-core</artifactId>
			<version>1.0.0-beta4</version>
		</dependency>
		<dependency>
			<groupId>org.nd4j</groupId>
			<artifactId>nd4j-cuda-9.2-platform</artifactId>
			<version>1.0.0-beta4</version>
		</dependency>
		<!--dependency>
			<groupId>org.nd4j</groupId>
			<artifactId>nd4j-native-platform</artifactId>
			<version>1.0.0-beta4</version>
		</dependency-->
		<dependency>
			<groupId>org.deeplearning4j</groupId>
			<artifactId>deeplearning4j-cuda-9.2</artifactId>
			<version>1.0.0-beta4</version>
		</dependency>
		<dependency>
			<groupId>org.datavec</groupId>
			<artifactId>datavec-jdbc</artifactId>
			<version>1.0.0-beta4</version>
		</dependency>

		<dependency>
			<groupId>me.joshmcfarlin</groupId>
			<artifactId>CryptoCompareAPI</artifactId>
			<version>master-SNAPSHOT</version>
		</dependency>
		<dependency>
			<groupId>com.github.jeffreytai</groupId>
			<artifactId>cryptocompare-api-wrapper</artifactId>
			<version>1.0.0</version>
		</dependency>
		<!-- https://mvnrepository.com/artifact/org.springframework/spring-web -->
		<dependency>
			<groupId>org.springframework</groupId>
			<artifactId>spring-web</artifactId>
			<version>5.1.8.RELEASE</version>
		</dependency>
		<!-- https://mvnrepository.com/artifact/com.fasterxml.jackson.core/jackson-databind -->
		<dependency>
			<groupId>com.fasterxml.jackson.core</groupId>
			<artifactId>jackson-databind</artifactId>
			<version>2.9.9.1</version>
		</dependency>

		<dependency>
			<groupId>com.squareup.retrofit2</groupId>
			<artifactId>retrofit</artifactId>
			<version>2.5.0</version>
		</dependency>

		<dependency>
			<groupId>com.squareup.retrofit2</groupId>
			<artifactId>converter-jackson</artifactId>
			<version>2.5.0</version>
		</dependency>

		<dependency>
			<groupId>org.apache.spark</groupId>
			<artifactId>spark-sql_2.10</artifactId>
			<version>${spark.version}</version>
			<exclusions>
				<exclusion>
					<groupId>org.slf4j</groupId>
					<artifactId>slf4j-log4j12</artifactId>
				</exclusion>
			</exclusions>
		</dependency>
		<dependency>
			<groupId>org.apache.spark</groupId>
			<artifactId>spark-mllib_2.10</artifactId>
			<version>${spark.version}</version>
			<exclusions>
				<exclusion>
					<groupId>org.slf4j</groupId>
					<artifactId>slf4j-log4j12</artifactId>
				</exclusion>
			</exclusions>
		</dependency>
		<dependency>
			<groupId>org.apache.spark</groupId>
			<artifactId>spark-core_2.10</artifactId>
			<version>${spark.version}</version>
			<exclusions>
				<exclusion>
					<groupId>org.slf4j</groupId>
					<artifactId>slf4j-log4j12</artifactId>
				</exclusion>
			</exclusions>
		</dependency>
		<dependency>
			<groupId>org.jfree</groupId>
			<artifactId>jfreechart</artifactId>
			<version>${jfreechart.version}</version>
		</dependency>
		<!-- Guava dependency -->
		<dependency>
			<groupId>com.google.guava</groupId>
			<artifactId>guava</artifactId>
			<version>${guava.version}</version>
		</dependency>
	</dependencies>

	<build>
		<plugins>
			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-javadoc-plugin</artifactId>
				<configuration>
					<minmemory>128m</minmemory>
					<maxmemory>512m</maxmemory>
				</configuration>
			</plugin>
		</plugins>
	</build>
</project>

Compiling with Java 8 instead of Java 7: doesn't help.

I think there is my problem. The cuda driver is throwing errors. Guess I was under the false impression that CUDA-Z means everything is fine with the driver. Apparently the driver is too old but because there is no newer one Guess I will need to switch to an even older cuda then 9.2.

Downgrading to cuda 8.0 did the trick. But now ND4J just straight up tells me: CUDA backend requires compute capatibility of 3.0 and above to run.

Card is simply too old. I'll play around with downgrading cuda as well, because after all this time i would like to see it actually run something.. probably slower then the CPU anyway.