The Next Phase Of Machine Learning


Machine learning is all about doing complex calculations on huge volumes of data with increasing efficiency, and with a growing stockpile of success stories it has rapidly evolved from a rather obscure computer science concept into the go-to method for everything from facial recognition technology to autonomous cars. [getkc id="305" kc_name="Machine learning"] can apply to every corporate fu... » read more

Making Machine Learning Portable


Machine learning is everywhere, and it has exploded at a pace no one would have expected. Even a year ago, ML was more of an experiment than a reality. NVIDIA's stock price (Fig. 1, below) is a good representation of just how quickly this market has grown. GPUs are the chip of choice for training machine learning systems. Fig. 1: Nvidia 5-year stock price. Source: Google Finance Ma... » read more

Toward System-Level Test


The push toward more complex integration in chips, advanced packaging, and the use of those chips for new applications is turning the test world upside down. Most people think of test as a single operation that is performed during manufacturing. In reality it is a portfolio of separate operations, and the number of tests required is growing as designs become more heterogeneous and as they ar... » read more

Using An Integrated Subsystem To Accelerate Data Fusion In Your SoC


The fusion of sensor data, voice, audio and biometrics is constantly increasing the processing requirements for applications in mobile, automotive and IoT markets. Next-generation digital sensors require higher bandwidths, and more advanced voice detection and speech recognition algorithms are driving the development of progressively more complex embedded ICs. Sensor fusion to data fusion T... » read more

Age Of Acceleration


A shift from the fastest processors to accelerating specific functions is underway, supplanting an era of dark silicon in which one or more processor cores remain in a ready state whenever a single core's performance bogs down. In effect, the dark silicon/multi-core approach is being scrapped for many functions in favor of an accelerator-based microarchitecture that is far more granular. The... » read more

Hardware/Software Tipping Point


It doesn't matter if you believe [getkc id="74" comment="Moore's Law"] has ended or is just slowing down. It is becoming very clear that design in the future will be significant different than it is today. Moore's law allowed the semiconductor industry to reuse design blocks from previous designs, and these were helped along by a new technology node—even if it was a sub-optimal solution. I... » read more

The Efficiency Problem


Part one of this report addressed the efficiency problem in neural networks. This segment addresses efficiencies in training, quantization, and optimizing the network and the hardware. Minimize the Bits (CNN Advanced Quantization) Training a CNN involves assigning weight vectors to certain results, and applying adaptive filters to those results to determine the positives, false positives, a... » read more

The Multiplier And The Singularity


In 1993, Vernor Vinge, a computer scientist and science fiction writer, first described an event called the Singularity—the point when machine intelligence matches and then surpasses human intelligence. And since then, top scientists, engineers and futurists have been asking just how far away we are from that event. In 2006, Ray Kurzweil published a book, "The Singularity is Near," in whic... » read more

Tuning Heterogeneous SoCs


It's one thing to pack multiple processor cores into a design, but it is much more difficult to ensure the hardware matches the software's requirements, or that the software optimally uses the hardware. Both the hardware and software teams are now facing these issues, and there are few tools to help them fully understand the problems or to provide solutions. Design teams continue to add more... » read more

Teaching Computers To See


Vision processing is emerging as a foundation technology for a number of high-growth applications, spurring a wave of intensive research to reduce power, improve performance, and push embedded vision into the mainstream to leverage economies of scale. What began as a relatively modest development effort has turned into an all-out race for a piece of this market, and for good reason. Mark... » read more

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