As formal verification becomes more common in the industry, design complexity continues to be a challenge. Article argues that this is a byproduct of design-centric approach (optimize area, power, speed) without considering verifiability. A verification-centric approach driven by polynomial formal verification analysis can produce verifiable designs.

Abstract: Recently, a lot of effort has been put into developing formal verification approaches by both academic and industrial research. In practice, these techniques often give satisfying results for some types of circuits, while they fail for others. A major challenge in this domain is that the verification techniques suffer from unpredictability in their performance. The only way to overcome this challenge is the calculation of bounds for the space and time complexities. If a verification method has polynomial space and time complexities, scalability can be guaranteed. In this tutorial paper, we review recent developments in formal ve

cross-posted from: https://discuss.tchncs.de/post/8824219

One way to help alleviate the effects of the talent shortage is changing how semiconductors are designed so that organizations can achieve more with their existing workforce. This requires moving away from project-centric design and transitioning to an IP-centric design methodology.

Over the past few years, teams have moved from building relatively self-contained, isolated designs to creating complex platforms across dispersed and integrated design centers. Larger design footprints, a more comprehensive array of products and quicker time to market are other contributing factors to walking away from a project-based design methodology.

One way to help alleviate the effects of the talent shortage is changing how semiconductors are designed so that organizations can achieve more with their existing workforce. This requires moving away from project-centric design and transitioning to an IP-centric design methodology.

Over the past few years, teams have moved from building relatively self-contained, isolated designs to creating complex platforms across dispersed and integrated design centers. Larger design footprints, a more comprehensive array of products and quicker time to market are other contributing factors to walking away from a project-based design methodology.

For battery-operated devices, the energy consumption for chip production far exceeds the lifetime energy consumption of the chips themselves. So, if we want to save energy, we’d better focus on the manufacturing process, argues Bram Nauta.

So how can universities train students for a continuous and rapidly changing technology? This is especially difficult because it involves both software and hardware, and more domain-specific and increasingly heterogeneous architectures. And regardless of whether these devices are tethered to a battery or plugged into a socket, they need to be much more energy-efficient. Given the slowdown in Moore’s Law and the shrinking power, performance and area/cost benefits of scaling, that often requires a mix of computer science, electrical engineering, and in packages, an increasing amount of mechanical engineering.

“Mechanical engineers, electrical engineers, those disciplinary trainings through those curriculums, they’re accredited and we have a very vigorous process that will continue. But these smaller, bite-sized chunks of curriculum will allow a student to broaden. So as a mechanical engineer, I may not necessarily have either capacity in my studies, or the depth of interest, to take an

Exascale is the next frontier in computing power, where systems are built to carry out extremely complex functions with increased speed and precision. This in turn enables researchers to accelerate their work into some of the most pressing challenges we face, including the development of new drugs, and advances in nuclear fusion to produce potentially limitless clean low-carbon energy.

The exascale system hosted at the University of Edinburgh will be able to carry out these complicated workloads while also supporting critical research into AI safety and development, as the UK seeks to safely harness its potential to improve lives across the country.

cross-posted from: https://discuss.tchncs.de/post/3979328

Engineers in Princeton managed to train GPT4 and extend AutoSVA to generate SVA (systemverilog assertions) from buggy RTL and functionality description. SVA is widely used to verify digital design for ASIC and FPGAs. AutoSVA2, which extends open-source AutoSVA, improves the flow to generate SVA from English description. LLM was trained in multiple iterations to generate SVA with correct syntax, which is something GPT fails to do by itself. Authors argue that GPT's "creativity" allows it to write correct assertion even from a buggy RTL. Later authors used this tool to write RTL from scratch as well. RTL written by GPT was tested against the SVA generated by this tool, and SVA corrected by an engineer was fed back to LLM, which generated functionally correct FIFO queue in a few iterations.

Abstract—Formal property verification (FPV) has existed for decades and has been shown to be effective at finding intricate RTL bu

Engineers in Princeton managed to train GPT4 and extend AutoSVA to generate SVA (systemverilog assertions) from buggy RTL and functionality description. SVA is widely used to verify digital design for ASIC and FPGAs. AutoSVA2, which extends open-source AutoSVA, improves the flow to generate SVA from English description. LLM was trained in multiple iterations to generate SVA with correct syntax, which is something GPT fails to do by itself. Authors argue that GPT's "creativity" allows it to write correct assertion even from a buggy RTL. Later authors used this tool to write RTL from scratch as well. RTL written by GPT was tested against the SVA generated by this tool, and SVA corrected by an engineer was fed back to LLM, which generated functionally correct FIFO queue in a few iterations.

Abstract—Formal property verification (FPV) has existed for decades and has been shown to be effective at finding intricate RTL bugs. However, formal properties, such as those written as SystemVerilog

One of the biggest shortcomings of silicon is that it can only be made so thin because its material properties are fundamentally limited to three dimensions [3D]. For this reason, two-dimensional [2D] semiconductors—so thin as to have almost no height—have become an object of interest to scientists, engineers and microelectronics manufacturers.

Thinner chip components would provide greater control and precision over the flow of electricity in a device, while lowering the amount of energy required to power it. A 2D semiconductor would also contribute to keeping the surface area of a chip to a minimum, lying in a thin film atop a supporting silicon device.

But until recently, attempts to create such a material have been unsuccessful.

Now, researchers at the University of Pennsylvania School of Engineering and Applied Science have grown a high-performing 2D semiconductor to a full-size, industrial-scale wafer. In addition, the semiconductor material, indium selenide (InSe), can be d

The key takeaway here is that the people writing these guidelines try to give as much information as possible,” Reaves says. “That’s great, in theory. But the writers don’t prioritize the advice that’s most important. Or, more specifically, they don’t deprioritize the points that are significantly less important. And because there is so much security advice to include, the guidelines can be overwhelming – and the most important points get lost in the shuffle.

In other words, the guideline writers are compiling security information, rather than curating security information for their readers.

Drawing on what they learned from the interviews, the researchers developed two recommendations for improving future security guidelines.

First, guideline writers need a clear set of best practices on how to curate information so that security guidelines tell users both what they need to know and how to prioritize that information.

Second, writers – and the computer security community

As solder bump pitches shrink, several issues arise. Reduced bump height and surface area for bonding make it increasingly difficult to establish reliable electrical connections, necessitating precise manufacturing processes to avoid errors. Critical co-planarity and surface roughness become paramount, as even minor irregularities can compromise successful bonding.

To overcome these issues, Cu-Cu hybrid bonding technology steps in as a game-changer. This innovative technique involves embedding metal contacts between dielectric materials and using heat treatment for solid-state diffusion of copper atoms, thereby eliminating the bridging problem associated with soldering.

The advantages of hybrid bonding over flip-chip soldering are obvious. Firstly, it enables ultra-fine pitch and small contact sizes, facilitating high I/O counts. This is critical in modern semiconductor packaging, where devices require a growing number of connections to meet performance demands. Secondly, unlike flip

cross-posted from: https://discuss.tchncs.de/post/3306215

Although you are probably not aware of them, dozens of electronic control units (ECUs) — printed circuit boards (PCBs) in metal or plastic housings — exist in your car to control and monitor the operation and safety of your vehicle’s many control systems. These units must work for the lifetime of your car, during which time they are subjected to many heating and cooling cycles. The most obvious cycle occurs when you start your car after it has cooled at night. It heats up as the car runs and then cools again when you shut it off. That’s one “ambient” temperature cycle.

Additional so called “active” thermal cycles can occur locally within specific electronic components on the PCB. For instance, a MOSFET transistor draws a lot of current and heats up the PCB near its location, causing additional thermal cycling. These complex temperature distributions can cause local thermomechanical strain because differences in temperat

Although you are probably not aware of them, dozens of electronic control units (ECUs) — printed circuit boards (PCBs) in metal or plastic housings — exist in your car to control and monitor the operation and safety of your vehicle’s many control systems. These units must work for the lifetime of your car, during which time they are subjected to many heating and cooling cycles. The most obvious cycle occurs when you start your car after it has cooled at night. It heats up as the car runs and then cools again when you shut it off. That’s one “ambient” temperature cycle.

Additional so called “active” thermal cycles can occur locally within specific electronic components on the PCB. For instance, a MOSFET transistor draws a lot of current and heats up the PCB near its location, causing additional thermal cycling. These complex temperature distributions can cause local thermomechanical strain because differences in temperature across the PCB result in differential expansion of the board.

Mine is playing AOE2 in easiest (or standard if I want a bit of challenge) mode against 3 bots. I just build my economy, wall up (and laugh at the enemy soldiers attacking my walls in vain), reach imperial age and attack once my army reaches the population limit. I also send 104 in the chat so they don't surrender and I can enjoy razing their all buildings one by one. If any of them builds a castle, even more fun. A build a trebuchet and watch it raze the castle from a safe distance. If there is sea, after I am done with the land, I build 3 docks, do research and build a navy and hunt down ships around the unxplored sea. It is fun, satisfying and relaxing.

What is yours?

cross-posted from: https://discuss.tchncs.de/post/3157319

Compared with traditional monolithic devices, the design and manufacturing process for chiplets is significantly different. The scrap costs associated with manufacturing traditional monolithic semiconductor devices is basically linear, including single chip cost, packaging, and assembly costs.

Manufacturing processes for 2.5D/3D designs differ significantly in terms of the accumulation of scrap costs. Specifically, these costs increase geometrically from fabrication to assembly driven by scrap costs for multiple dies, multi-chip partial assemblies, and/or full 2.5D/3D packages.

Shifting tests, either left or right, in the test process is a strategy to achieve these goals and minimize the overall manufacturing cost of 2.5D/3D components. Shift left is the ability to increase test coverage earlier in the manufacturing process (e.g., during wafer inspection and partial packaging) to maximize KGD, while reducing future

Compared with traditional monolithic devices, the design and manufacturing process for chiplets is significantly different. The scrap costs associated with manufacturing traditional monolithic semiconductor devices is basically linear, including single chip cost, packaging, and assembly costs.

Manufacturing processes for 2.5D/3D designs differ significantly in terms of the accumulation of scrap costs. Specifically, these costs increase geometrically from fabrication to assembly driven by scrap costs for multiple dies, multi-chip partial assemblies, and/or full 2.5D/3D packages.

Shifting tests, either left or right, in the test process is a strategy to achieve these goals and minimize the overall manufacturing cost of 2.5D/3D components. Shift left is the ability to increase test coverage earlier in the manufacturing process (e.g., during wafer inspection and partial packaging) to maximize KGD, while reducing future packaging costs. Additional tests can also be added to the process to

cross-posted from: https://discuss.tchncs.de/post/3011500

Many volume applications use FPGA because they need in-field reconfigurability (changing standards, changing algorithms, etc) but they want to improve their system’s competitiveness (power, size, cost). FPGAs are bulky, expensive and power hungry. Integrating eFPGA can greatly improve the economics while maintaining full reconfigurability and performance.

We’ve found with customers that a significant portion of the LUTs in their designs don’t change with reconfigurations: they are fixed buses to bring data to and from the reconfigurable core. This can be hardwired so the number of LUTs needed in the SoC is typically half of what’s in the FPGA. There is also a lot of cost of voltage regulators for an FPGA that disappear with integration.

Typically, the cost of eFPGA is 1/10th the cost of the FPGA it replaces but with the same speed and programmability. Power can also be cut to 1/10th because most of the power in an

cross-posted from: https://discuss.tchncs.de/post/3011500

Many volume applications use FPGA because they need in-field reconfigurability (changing standards, changing algorithms, etc) but they want to improve their system’s competitiveness (power, size, cost). FPGAs are bulky, expensive and power hungry. Integrating eFPGA can greatly improve the economics while maintaining full reconfigurability and performance.

We’ve found with customers that a significant portion of the LUTs in their designs don’t change with reconfigurations: they are fixed buses to bring data to and from the reconfigurable core. This can be hardwired so the number of LUTs needed in the SoC is typically half of what’s in the FPGA. There is also a lot of cost of voltage regulators for an FPGA that disappear with integration.

Typically, the cost of eFPGA is 1/10th the cost of the FPGA it replaces but with the same speed and programmability. Power can also be cut to 1/10th because most of the power in an

Many volume applications use FPGA because they need in-field reconfigurability (changing standards, changing algorithms, etc) but they want to improve their system’s competitiveness (power, size, cost). FPGAs are bulky, expensive and power hungry. Integrating eFPGA can greatly improve the economics while maintaining full reconfigurability and performance.

We’ve found with customers that a significant portion of the LUTs in their designs don’t change with reconfigurations: they are fixed buses to bring data to and from the reconfigurable core. This can be hardwired so the number of LUTs needed in the SoC is typically half of what’s in the FPGA. There is also a lot of cost of voltage regulators for an FPGA that disappear with integration.

Typically, the cost of eFPGA is 1/10th the cost of the FPGA it replaces but with the same speed and programmability. Power can also be cut to 1/10th because most of the power in an FPGA is the power-hungry PHYs that are mostly not needed when using eF