Java Source Code Projects

    Java Source Code Projects is the general question asked by many students and researchers. We provide complete support for student’s source code projects. We introduce Java source code projects with the aim of offer effective codes for student’s academic projects. These projects give you the idea about latest technology and provide simple codes with guaranteed outputs. A range of tools, software, libraries, and frameworks are available and get complete project through online. We provides best development environment that not only support for source code, but also supports a complete range of project requirements (Abstract, Project Report, Project Explanation (online/offline), etc. Start to work with us and feel satisfaction.

Java Source Code Projects

    Java Source Code Projects contains HUB with a list of Java Source Code Projects. Java is a powerful development platform that allows you to customize the source code to your specific needs. Our experts follow a unique way of developing structure in a Java Source Code Projects. We created 1000+ Java Source Code Projects in the last year, which enable us to create applications for any fields. Readymade Java Source Code Projects are available for the following categories,

  • Java Programming Language Basics
  • Java Algorithms
  • Java Applets
  • Java GUI
  • Java Swing
  • Java Applications
  • Multithreading
  • Java Garbage Collection
  • Java Utility Software and Tools
  • Java IEEE Domains

             -Java Image Processing

             -Java Data Mining

             -Java Cloud Computing

            -Java Services Computing

            -Java Networking

            -Java Big Data/Hadoop

            -Java GPU Computing


            -Java Web Mining

            -100+ Java Domains

Interesting Java Libraries Related to GPU

  • OpenGL (Low level application framework, which simplifies the FPGAs, GPUs, development
  • SystemML (Apache Incubator to support GPU)
  • TensorFlow (Open source Java library for Machine learning and Offloading to CUDA devices)
  • Jcuda (Alternative to CUDA4J )
  • DeepLearning 4j (JVM deep learning framework)
  • Nvidia libraries (Thrust, cuBLAS, cuDNN)


  • OpenCL 1.2 and OpenCL 2.0
  • Operating Systems (any)

                -Windows 32bit, 64bit

                -Linux 32bit, 64bit

                -Mac OSX 64bit

  • JNI Native Interface
  • Maven (if optional)

Supported Features of GPU in Java includes:

  • Exception handling
  • Single and multi-dimensional arrays
  • Static and instance fields
  • Dynamic memory allocation
  • Composite objects
  • Synchronized monitors and methods
  • Inner classes and strings
  • Multi-GPU Support
  • GPU on Apache Spark with Deeplearning 4j
  • Real-Time Analytics (Supply Chain, Retail)

Commercial/Open Source GPU Databases

  • MapD (Commercial)
  • Kinetica (Commercial)
  • Blazegraph (Commercial)
  • BlazingDB (Open Source)
  • PG-Storm (Open Source)

Major Research Fields using Java

  • Accelerated Analytics
  • Deep Learning
  • NLP based Full-Text Search
  • Native IP & GIS Address Object Support
  • Real-Time Data Handling (Structured/Unstructured)
  • Multi-Label Classification
  • Data Analytics and Processing
  • Deep Integration + other frameworks









  • Manufacturing IoT

                 -Avoid failures and ensure safety

                 -Live streaming analytics

                 -Defect detection

                 -Monitor and track inventory

                 -Track quality, warranty claims and returns

Recent Project Titles in GPU Computing

  • An efficacious performance of GPU-Accelerated Parallel Hierarchical Extreme Learning Machine based on Flink for Big Data
  • On the use of Iterative Computation Spark for GPU in-Memory based Processing
  • An effectual mechanism of GPU Parallel Implementation for Spatially Adaptive Hyperspectral by Image Classification
  • A new source of Cooperative DVFS for energy-efficient HEVC decoding based on embedded CPU-GPU architecture
  • An innovative method for Latency-aware packet processing based on by CPU-GPU heterogeneous systems
  • The new process of Consensus Gene Selection Criteria for Distributed GPU Partial Least Squares-based on Gene Microarray Analysis in Diffused Large B Cell Lymphoma (DLBCL) and related findings
  • An inventive method of Acceleration via Inline Cache for Memory-Intensive Algorithms in FPGA of High-Level Synthesis
  • The fresh mechanism for Energy efficient real-time task scheduling based on CPU-GPU hybrid clusters
  • On the use of SDAccel and comparison to GPUs and multicore CPUs based on Exploration of OpenCL for FPGAs
  • An ingenious method for GPU parallel neural hierarchical multi objective solver of burst routing and wavelength assignment
  • An effective system for large-sized image segmentation based on a new optimized GPU version of k-means algorithm
  • A modern mechanism for GPU base calling function of DNA based on strand sequencing
  • An efficient process of ultrasound pressure fields based on GPU simulator
  • A new process of Fast intra coding unit size decision for HEVC with GPU based on keypoint detection
  • The fresh method of cudaCR In-Kernel Application-Level Checkpoint/Restart Scheme for CUDA-Enabled GPUs