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
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“…software is changing at head-spinning rates, driven by advances in how computers process giant amounts of data using artificial-intelligence techniques,” said the Wall Street Journal in a recent article, highlighting the challenge faced by smartphone software developers.
We agree, and it’s not just in smartphones. BDTI is seeing this trend across a wide range of applications. Visual intelligence, supported by sophisticated hardware and sensors, and delivered to users through increasingly
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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
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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-
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Earlier this week, Google announced the spin-off of its self-driving car project into a stand-alone business. Will Google become a major player in the automotive industry? Today, that idea seems far-fetched. On the other hand, 15 years ago Apple was a personal computer company, and few would have guessed that it would eventually become a dominant player in consumer electronics and photography.
The Google announcement resonated with me in light of a fascinating recent presentation by Mark
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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
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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-
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Programmable logic IP cores, intended for integration within a broader-function ASIC, are a long-discussed and –explored product option that has yet to achieve more than niche adoption. Small FPGA IP players such as Flex Logic Technologies and Menta linger in the market, but picking such a supplier for your next SoC can be a gamble; what happens if they get acquired or otherwise disappear? And big FPGA vendors like Altera (now Intel's Programmable Solutions Group) and Xilinx, along with medium-
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For humans, it goes without saying that vision is extremely valuable. When you stop to think about it, it’s remarkable what a diverse set of capabilities is enabled by human vision – from reading facial expressions, to navigating complex three-dimensional spaces (whether by foot, bicycle, car, or otherwise), to performing intricate tasks like threading a needle.
One of the reasons why I’m so excited about the potential of computer vision is that I believe that it will bring a similar range of
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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
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