High performance algorithms for large scale placement problem

Placement is one of the most important problems in electronic design automation (EDA). An inferior placement solution will not only affect the chip’s performance but might also make it nonmanufacturable by producing excessive wirelength, which is beyond available routing resources. Although placement has been extensively investigated for several decades, it is still a very challenging problem mainly due to that design scale has been dramatically increased by order of magnitudes and the increasing trend seems unstoppable. In modern design, chips commonly integrate millions of gates that require over tens of metal routing layers. Besides, new manufacturing techniques bring out new requests leading to that multi-objectives should be optimized simultaneously during placement. Our research provides high performance algorithms for placement problem. We propose (i) a high performance global placement core engine POLAR; (ii) an efficient routability-driven placer POLAR 2.0, which is an extension of POLAR to deal with routing congestion; (iii) an ultrafast global placer POLAR 3.0, which explore parallelism on POLAR and can make full use of multi-core system; (iv) some efficient triple patterning lithography (TPL) aware detailed placement algorithms

Architectural Impacts of RFiop: RF to Address I/O Pad and Memory Controller Scalability

Despite power boundaries, Moore's law is still present via scaling the number of cores, which keeps adding demands for more memory bandwidth (MBW) requested by these cores. To obtain higher MBW levels, it is fundamental to address memory controller (MC) scalability. However, MC scalability growth is limited by I/O pin counts scaling. To underline MC and pin scaling, a radio frequency(RF) I/O pad-scalable package-based (RFiop) memory organization is further investigated. In RFiop, a RF pad (RFpad) is defined as a quilt-packaging (QP) coplanar waveguide employed at RF ranges. An RFpad connects a rank to an RFMC which is formed by coupling MCs to RF transmitter/receivers. By using QP package to explore the architectural benefits of laying out ranks, RFiop replaces the traditional memory path with an RF-based one, while exploring the scalability of RFpads/RFMCs via RF signaling. When evaluating RFiop, our findings show that MBW/performance are enhanced by around 4.3x which can be viewed as a diminution in transaction queue occupancy/latency as well as using a reduced and scalable 4-8 RFpads per RFMC. RFiop architectural area benefits allow MBW/performance improvements of around 3.2x, while reducing interconnection energy up to 78%

High Efficiency Polymer based Direct Multi-jet Impingement Cooling Solution for High Power Devices

Liquid jet impingement cooling is an efficient cooling technique where the liquid coolant is directly ejected from nozzles on the chip backside resulting in a high cooling efficiency due to the absence of the TIM and the lateral temperature gradient. In literature, several Si-fabrication based impingement coolers with nozzle diameters of a few distributed returns or combination of micro-channels and impingement nozzles. The drawback of this Si processing of the cooler is the high fabrication cost. Other fabrication methods for nozzle diameters for ceramic and metal. Low cost fabrication methods, including injection molding and 3D printing have been introduced for much larger nozzle diameters (mm range) with larger cooler dimensions. These dimensions and processes are however not compatible with the chip packaging process flow. This PhD focuses on the modeling, design, fabrication and characterization of a micro-scale liquid impingement cooler using advanced, yet cost efficient, fabrication techniques. The main objectives are: (a) development of a modeling methodology to optimize the cooler geometry; (b) exploring low cost fabrication methods for the package level impingement jet cooler; (c) experimental thermal and hydraulic characterization and analysis of the fabricated coolers; (d) applying the direct impingement jet cooling solutions to different applications

VLSI Design

This book provides some recent advances in design nanometer VLSI chips. The selected topics try to present some open problems and challenges with important topics ranging from design tools, new post-silicon devices, GPU-based parallel computing, emerging 3D integration, and antenna design. The book consists of two parts, with chapters such as: VLSI design for multi-sensor smart systems on a chip, Three-dimensional integrated circuits design for thousand-core processors, Parallel symbolic analysis of large analog circuits on GPU platforms, Algorithms for CAD tools VLSI design, A multilevel memetic algorithm for large SAT-encoded problems, etc

3rd Many-core Applications Research Community (MARC) Symposium. (KIT Scientific Reports ; 7598)

This manuscript includes recent scientific work regarding the Intel Single Chip Cloud computer and describes approaches for novel approaches for programming and run-time organization

High-performance Global Routing for Trillion-gate Systems-on-Chips.

Due to aggressive transistor scaling, modern-day CMOS circuits have continually increased in both complexity and productivity. Modern semiconductor designs have narrower and more resistive wires, thereby shifting the performance bottleneck to interconnect delay. These trends considerably impact timing closure and call for improvements in high-performance physical design tools to keep pace with the current state of IC innovation. As leading-edge designs may incorporate tens of millions of gates, algorithm and software scalability are crucial to achieving reasonable turnaround time. Moreover, with decreasing device sizes, optimizing traditional objectives is no longer sufficient. Our research focuses on (i) expanding the capabilities of standalone global routing, (ii) extending global routing for use in different design applications, and (iii) integrating routing within broader physical design optimizations and flows, e.g., congestion-driven placement. Our first global router relies on integer-linear programming (ILP), and can solve fairly large problem instances to optimality. Our second iterative global router relies on Lagrangian relaxation, where we relax the routing violation constraints to allowing routing overflow at a penalty. In both approaches, our desire is to give the router the maximum degree of freedom within a specified context. Empirically, both routers produce competitive results within a reasonable amount of runtime. To improve routability, we explore the incorporation of routing with placement, where the router estimates congestion and feeds this information to the placer. In turn, the emphasis on runtime is heightened, as the router will be invoked multiple times. Empirically, our placement-and-route framework significantly improves the final solution’s routability than performing the steps sequentially. To further enhance routability-driven placement, we (i) leverage incrementality to generate fast and accurate congestion maps, and (ii) develop several techniques to relieve cell-based and layout-based congestion. To broaden the scope of routing, we integrate a global router in a chip-design flow that addresses the buffer explosion problem.PHDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98025/1/jinhu_1.pd

HotSpot Thermal Floorplan Solver Using Conjugate Gradient to Speed Up

We proposed to use the conjugate gradient method to effectively solve the thermal resistance model in HotSpot thermal floorplan tool. The iterative conjugate gradient solver is suitable for traditional sparse matrix linear systems. We also defined the relative sparse matrix in the iterative thermal floorplan of Simulated Annealing framework algorithm, and the iterative method of relative sparse matrix could be applied to other iterative framework algorithms. The experimental results show that the running time of our incremental iterative conjugate gradient solver is speeded up approximately 11x compared with the LU decomposition method for case ami49, and the experiment ratio curve shows that our iterative conjugate gradient solver accelerated more with increasing number of modules