10x acceleration

10x acceleration

Stream processing can be accelerated with multiple servers or multiple processing cores. The first approach, high-performance computing (HPC), relies on optimization techniques such as load balancing, clustering, edge computing, and more. The second approach is using the 1000s of cores found in GPU for general programming.


Reality Frontier can achieve a multi-fold speed up of your algorithms. We can also assist with your infrastructure needs, either using commodity hardware or a managed hosted solution. The cost of scaling out to many-core is significantly lower than using multiple servers.

Where to go from here?

1. Check that parallel programming is a fit for your needs

Stream Processing on many-core chipsets is a programming model that speeding up applications by 10 times and up. What does it take?

Compute-intense applications can be recognized by their compute to I/O ratio. When an application loads or stores a piece of data rarely compared to the number of computations performed on it, the application is considered compute-intensive.

Applications are said to be data parallel when the operations they perform on a dataset can be applied on each of its data items independently from the others. Data parallelism allows applying an operation on several data items at the same time.

Finally, an application exposes data locality when the data it produces is read or written at most once or twice and then never again. This is very common in signal processing applications, such as video and audio filters.

If your application fits these criteria, you may consider a stream-processing implementation with RealityFrontier.

2. Start with a prototype with us – free of charge

Hardware Acceleration

  • Real-time image and signal processing
  • Acceleration using NVIDA CUDA, OpenCL, C++
  • Inexpensive compute appliances

Stream Processing

  • Dataflow modeling and large-scale calculation
  • Distributed parallel programming with pthreads, MPI
  • Instrumentation and optimization of parallel processes

System engineering

  • High-performance with Windows 2008, Windows Azure, Amazon EC2
  • Transaction optimization for database systems and enterprise service bus
  • Infrastructure topology, scalability, distribution, mobility, metering

3. Accelerate your application

Engage us for HPC benchmarking and CUDA programming.

Our other services

3D visual computing

For visualization, scientific modeling, machine vision.

Mobile apps

To optimize the interaction with the physical world.

More on the web

  • Stream processing – Designing “in parallel”
  • GPGPU – General purpose GPU
  • CUDA – Parallel programming with NVIDIA
  • OpenCL – Open standard version of CUDA
  • APP SDK – Parallel programming with AMD