Build the Most Powerful Data-Centric Applications with Kalray
MPPA® Accelerator Use Cases
AI & Machine Learning
Why Kalray for Machine Learning?
- Offload computational AI workloads
- Unprecedented programmability
- Best performance per watt and per $
Training & Inference
Machine learning enables computers to learn from data and make predictions or decisions without being explicitly programmed. The application of machine learning is a multi-step process: the first step, training the model with a reference labeled data set, adapts the parameters to the expected function. In the second step, called inference, the trained model is deployed and applied to new data, to enable decision making.
Offloading GPUs
From an implementation standpoint, training takes place offline, in data centers on servers accelerated by GPU-like processors or specialized hardware. For the inference part of AI, these processors are not sufficient, and here is where MPPA makes the difference: Kalray accelerators enhance AI inference by efficiently offloading and accelerating specific tasks, such as image processing and data preprocessing, resulting in faster and more power-efficient AI model execution.
MPPA Acceleration
Kalray’s acceleration cards provide the capability to efficiently and effectively offload the host CPU/GPU. Based on its MPPA® processor, Kalray’s K200 family of data‐centric acceleration cards offer an unprecedented level of performance and programmability for AI inference workloads, a game changer solution in terms of performance per Watt and per dollar.
Smart Vision
Why Kalray for Smart Vision?
- Offload computational AI workloads
- Unprecedented programmability
- Best performance per watt and per $
Capture, Process, Interpret
Smart vision is an AI application that utilizes computer vision techniques to enable machines to capture, process, and interpret visual information from the physical world, enabling tasks like image analysis, object recognition, and quality control. Smart vision applications are deployed across all industries.
Sustainable Manufacturing
With AI enabled smart vision, we are witnessing the biggest progression in automation since the introduction of the moving assembly line. Smart vision applications have a major impact on society as they enable smarter and safer cities with more efficient transport, they help us reduce our footprint with more sustainable manufacturing processes and they allow us to better respond to new diseases and provide better healthcare.
Boost Efficiency
Kalray accelerators play a crucial role in enhancing machine vision capabilities. By offloading computational workloads from the CPU or GPU, they significantly improve the speed and efficiency of smart vision applications. Kalray accelerators are particularly valuable in edge computing scenarios, where low latency and high throughput are essential, enabling devices like cameras and drones to process images and make intelligent decisions locally without relying heavily on cloud-based resources. This efficiency boost not only enhances the real-time capabilities of smart vision systems but also conserves energy and reduces the latency associated with cloud-based processing.
5G/Edge Computing
Why Kalray for 5G/Edge Computing?
- Optimized for edge computing scenarios
- Analyze data where it is generated
- Best performance per watt and per $
Processing At the Edge
Edge computing is booming and thanks to the possibilities created by 5G networks, the growth of edge computing will accelerate exponentially. We talk about edge computing when data is processed and stored closer to the sources of data, rather than transferring the data to central data centers or the cloud. Organizations process data at the edge when latency is critical or to conserve bandwidth.
Maximize Efficiency
Data centers at the edge are typically limited in capacity and as such need maximal efficiency. Kalray enables customers to process data at the edge smarter, faster and more efficiently. Kalray’s patented MPPA technology and acceleration cards provide the capability to capture and perform inline analysis of a very large amount of data, close to where data is generated, to extract useful information from this flow of data and to react in real time based on this data.
Intelligent Data Centers
Why Kalray for Intelligent Data Centers?
- Heterogenous multi-processing
- Offload host CPUs/GPUs
- Best performance per watt and per $
Performance & Efficiency
Data centers are growing massively due to the surge of data to be processed, applications to process the data and users who need to access these applications, often from remote locations. As a result, data center managers are under constant pressure to meet performance, scalability and efficiency requirements. To continue bringing high value to their demanding customers, data centers are seeking composable, highly efficient and heterogeneous, multi-processing and adaptive solutions, both on storage nodes and compute nodes.
Multiple Workloads
General purpose CPUs have hit their physical limitations as they can only support single threaded user applications. GPUs were not designed for dealing with multiple workloads and their data efficiently. Intelligent data centers need a new class of processing accelerator to efficiently run the predominantly data-centric heterogeneous processing tasks and offload main CPUs.
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WHITE PAPER
A new generation of processor is needed to support the “explosion of data” we’re experiencing today
