processors

Himax, CEVA, emza Partner to Develop Low Power Vision Processing Platform

Image-sensor maker Himax, processor core vendor CEVA, and algorithm provider emza Visual Sense have partnered to develop a low-power "always on" vision sensor module with integrated visual analytics. The three companies offered a conceptual demonstration of the product, dubbed the WiseEye IoT vision sensor, at last month's Consumer Electronics Show. Assuming that WiseEye IoT is able to perform with sufficient accuracy and frame rates, with its target power consumption of 5-10 mW for common Read more...

Case Study: Deep Understanding of Processor Architectures and Computer Vision Algorithms is Key to a Breakthrough Product

Computer vision promises to be the key to the next set of "killer apps"—computer vision-enabled apps that will leverage artificial intelligence to help keep us safer and healthier. But computer vision algorithms are compute- and power-intensive, and need to process large amounts of data. These barriers have limited their use to enterprise, line-powered devices and cloud-assisted mobile devices. The implementation of computer vision algorithms on mobile processors, where compute resources are Read more...

New AMD Software Library, Hardware Support Deep Learning Acceleration

HPC (high-performance computing) servers, which have notably embraced the GPGPU (general-purpose computing on graphics processing units) concept in recent years, are increasingly being employed for computer vision and other deep learning-based applications. Beginning in late 2014, NVIDIA supplemented its general-purpose CUDA toolset for GPU-accelerated heterogeneous computing with its proprietary CuDNN software library, which codifies the basic mathematical and data operations at the core of Read more...

Qualcomm's Latest Snapdragon Enhancements Heavily Leverage a Lithography Shrink

Qualcomm formally unveiled the Snapdragon 835, its latest premium-tier mobile processor, at the Consumer Electronics Show earlier this month after a last-fall "tease". Sporting eight CPU cores and fabricated in Samsung’s latest 10 nm process, the new chip represents the next step in the evolution of the Snapdragon 800 product line, building on features previously introduced in the Snapdragon 820 and 821. The 14 nm-fabricated Snapdragon 820, initially unveiled in March 2015 with fuller Read more...

CEVA-X1 DSP Core Targets Cellular IoT Opportunities

In March, InsideDSP covered the CEVA-X4, the first member of the company's cellular DSP core family based on its CEVA-X architecture framework, and focused on smartphones and tablets that support gigabit-per-second LTE-Advanced and LTE-A Pro protocols. In June, the company introduced the CEVA-X2, with half the scalar units of its bigger sibling (two versus four), and targeting wearables and other devices that harness 10 Mbps LTE-Cat 1 (formerly known as LTE-M Category 1). And now the company Read more...

AMD's ROCm: CUDA Gets Some Competition

NVIDIA was an early and aggressive advocate of leveraging graphics processors for other massively parallel processing tasks (often referred to as general-purpose computing on graphics processing units, or GPGPU). The company's CUDA software toolset for GPU computing has to date secured only modest success in mobile and desktop PCs; with game physics processing acceleration, for example, along with still and video image processing acceleration. However, GPGPU has been embraced in the HPC (high- Read more...

Case Study: Balancing the Demands of Algorithms and the Capabilities of Processors When Designing Computer Vision Systems

There is now little question that deep learning is an effective means for a wide range of detection and recognition applications. It is increasingly used in computer vision, where it has vastly improved accuracy rates for object recognition. In some cases, the effectiveness of deep learning has also resulted in unrealistic—or, as-yet unrealizable—expectations. For example, one customer came to BDTI with a long list of detection and recognition functions that it wanted implemented on a low-cost Read more...

Wave Computing Targets Deep Learning

Look back over the history of processors, and you'll see many examples of tasks initially restricted to running on high-end processors that, once they became popular and standardized, eventually attracted specialized co-processor or processor support (Figure 1). Consider, for example, video encoding and decoding, nowadays efficiently handled by a multimedia co-processor core sitting alongside the main processor in a SoC. Or consider graphics processing; initially, only BitBlt and other bitmap- Read more...

Case Study: Careful Analysis Leads to Successful Products

Processor vendors and system designers share a common concern: how to make sure their products meet customer needs. For processor vendors, a key challenge is to design architectures with enough performance to meet the demands of current and anticipated applications while staying within acceptable power and cost constraints, and enabling good software developer productivity. Fundamentally, processor designers need to bring together the demands of algorithm workloads together with the Read more...

The CEVA-XM6 Vision Processor Core Boosts Performance for Embedded Deep Learning Applications

Hard on the heels of the public release of CEVA's second-generation convolutional neural network toolset, CDNN2, the company is putting the final touches on its fifth-generation processor core, the CEVA-XM6, designed to run software generated by that toolset. Liran Bar, the company's Director of Product Marketing, acknowledged in a recent briefing that the new core represents an evolutionary step, versus revolutionary break, from its predecessors: the CEVA-MM3101 (introduced in 2012) and the Read more...