MapD Makes GPUs First-Class Citizens

It’s now well known that with the latest innovations in parallel programming and GPU technology, graphics processing units (GPUs) can be harnessed today to deal with the enormous data sets regularly encountered in applications ranging from ADAS, artificial intelligence, and gaming to deep learning, scientific computation, and high-performance computing. But how exactly do you find what you... » read more

GPUs Power Ahead

GPUs, long a sideshow for CPUs, are suddenly the rising stars of the processor world. They are a first choice in everything from artificial intelligence systems to automotive ADAS applications and deep learning systems powered by [getkc id="261" kc_name="convolutional neural network"]. And they are still the mainstays of high-performance computing, gaming and scientific computation, to name ... » read more

Rethinking Processor Architectures

The semiconductor industry's obsession with clock speeds, cores and how many transistors fit on a piece of silicon may be nearing an end for real this time. The [getentity id="22048" comment="IEEE"] said it will develop the International Roadmap for Devices and Systems (IRDS), effectively setting the industry agenda for future silicon benchmarking and adding metrics that are relevant to specifi... » read more

New Metrics For The Cloud

Data centers are beginning to adjust their definition of what makes one server better than another. Rather than comparing benchmarked performance of general-purpose servers, they are adding a new level of granularity based upon what kind of chips work best for certain operations or applications. Those decisions increasingly include everything from the level of redundancy in compute operations, ... » read more

Capturing Performance

The challenge of working out the best performance for a given power budget is not a new one, but in many power-sensitive applications, the balance is tricky and requires sophisticated techniques. This is especially true in the media processor market where many systems companies are held back by power, energy and thermal issues. “It's really not a battery problem, it's a thermal problem... » read more

Executive Insight: Gideon Wertheizer

SE: From your standpoint, what’s the next big thing? Wertheizer: The industry was driven in the past few years by the structure the smartphone created. It looks like this area is about to grow. What’s changing is the integration of the smartphone with other applications. The smartphone is now a hub of entertainment and productivity with many devices connecting directly or indirectly to i... » read more

Power/Performance Bits: May 27

Battery captures waste heat, converts it to electricity While vast amounts of excess heat are generated by industrial processes and by electric power plants, researchers around the world have spent decades looking for ways to harness some of this wasted energy, according to engineering researchers at Stanford and MIT. They pointed out that most of these efforts have focused on thermoelectric d... » read more

Blog Review: Sept. 4

By Ed Sperling Cadence’s Brian Fuller looks at the opportunity for EDA in the cloud and where it’s most likely to gain traction. How about the PCB? Synopsys’ Mick Posner has moved beyond broad-based design ecosystems. He’s now reaching out to local neighborhoods with FPGA prototypes. Sounds like quality family time. Mentor’s Colin Walls concedes that all non-trivial software ... » read more

GPUs May Speed UP EDA Algorithms

The sequential EDA algorithms of old cannot keep pace with increasing design complexity, which is driving the industry to look at parallelism and other computational architectures such as the graphical processing unit (GPU). A 10X or 20X speedup for gate-level simulations means that a test that runs today in a week will run in less than a day, and a test that runs today in a month will run i... » read more

The Ubiquitous GPU

By Ann Steffora Mutschler No matter the application area, GPUs are likely playing a role like never before—even to accelerate EDA software algorithms. It’s no wonder given the ability of GPUs to handle parallel processing much more effectively than CPUs. And when coexisting in a heterogeneous system, GPUs allow the design team to maximize efficiency and performance by allocating tasks... » read more

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