Facing soaring enrollment and disruptive educational technologies, computing education increasingly relies on the contributions of teaching assistants (TAs), hence the critical importance of high-quality TA training. However, the design and implementation of TA training in computer science face substantial barriers, such as the lack of experienced TA trainers and the scarcity of relevant training materials.

Dynamic Partially Reconfiguration (DPR) on FPGA has attracted significant research interest in recent years since it provides benefits such as reduced area and flexible functionality. However, due to the lack of supporting synthesis tools in the current DPR design flow, leveraging benefits from DPR requires specific design expertise with laborious manual design effort. Considering the complicated concurrency relations among various functions, it is challenging to select appropriate Partial Reconfiguration Modules (PR Modules) and cluster them into proper groups with a proper reconfiguration schedule so that the hardware modules can be swapped in and out correctly during the run time. Furthermore, the design of PR Modules also impacts reconfiguration latency and resource utilization greatly. In this paper, we propose a Maximum-Weight Independent Set model to formulate the PR Module selection and clustering problem so that the original manual exploration can be solved efficiently and automatically. We also propose a step-wise adjustment configuration prefetching strategy incorporated in our model to generate optimized reconfiguration schedules. Our proposed approach not only supports various design constraints but also can consider multiple objectives such as area and reconfiguration delay. Experimental results show that our approach can optimize resource utilization and reduce reconfiguration delay with good scalability. Especially, the implementation of the real design case shows that our approach can be embedded in Xilinx's DPR design flow successfully.

We propose a collection of three shift-based primitives for building efficient compact CNN-based networks. These three primitives (channel shift, address shift, shortcut shift) can reduce the inference time on GPU while maintains the prediction accuracy. These shift-based primitives only moves the pointer but avoids memory copy, thus very fast. For example, the channel shift operation is 12.7× faster compared to channel shuffle in ShuffleNet but achieves the same accuracy. The address shift and channel shift can be merged into the point-wise group convolution and invokes only a single kernel call, taking little time to perform spatial convolution and channel shift. Shortcut shift requires no time to realize residual connection through allocating space in advance. We blend these shift-based primitives with point-wise group convolution and built two inference-efficient CNN architectures named AddressNet and Enhanced AddressNet. Experiments on CIFAR100 and ImageNet datasets show that our models are faster and achieve comparable or better accuracy.

Accelerators are becoming increasingly prevalent in distributed computation. FPGAs have been shown to be fast and power efficient for particular tasks, yet scheduling on FPGA-based multi-accelerator systems is challenging when workloads vary significantly in granularity in terms of task size and/or number of computational units required. We present a novel approach for dynamically scheduling tasks on networked multi-FPGA systems which maintains high performance, even in the presence of irregular tasks. Our topological ranking-based scheduling allows realistic irregular workloads to be processed while maintaining a significantly higher level of performance than existing schedulers.

This paper presents a novel approach for allocating resources in systems with multiple accelerators. It has three main contributions. First, a new model based on Birkhoff's representation theory in capturing the ordering properties of resource allocation requests (RArs). Second, an effective technique for resource allocation based on this model, targeting systems with multiple accelerators. Third, the evaluation of the proposed approach for Maxeler MPC-X multi-accelerator systems, demonstrating time-efficiency and 30%-50% failure-rate decrease (FRD) on random input dataset.

This paper presents a novel reconfigurable framework for training Convolutional Neural Networks (CNNs). The proposed framework is based on reconfiguring a streaming datapath at runtime to cover the training cycle for the various layers in a CNN. The streaming datapath can support various parameterized modules which can be customized to produce implementations with different trade-offs in performance and resource usage. The modules follow the same input and output data layout, simplifying configuration scheduling. For different layers, instances of the modules contain different computation kernels in parallel, which can be customized with different layer configurations and data precision. The associated models on performance, resource and bandwidth can be used in deriving parameters for the datapath to guide the analysis of design trade-offs to meet application requirements or platform constraints. They enable estimation of the implementation specifications given different layer configurations, to maximize performance under the constraints on bandwidth and hardware resources. Experimental results indicate that the proposed module design targeting Maxeler technology can achieve a performance of 62.06 GFLOPS for 32-bit floating-point arithmetic, outperforming existing accelerators. Further evaluation based on training LeNet-5 shows that the proposed framework achieves about 4 times faster than CPU implementation of Caffe and about 7.5 times more energy efficient than the GPU implementation of Caffe.

Novel device with multiple FPGAs on-chip based on interposer interconnection has emerged to resolve the IOs limit and improve the inter-FPGA communication delay. However, new challenges arise for the placement on such architecture. Firstly, existing work does not consider the detailed models for the path wirelength and delay estimation for interposer, which may significantly affect the placement quality. Secondly, previous work is mostly based on traditional tile-based placement which is slow for the placement of large design on multiple FPGAs.

With the development of technology, the architecture of embedded systems is no longer homogeneous. Some of them integrate multi-core processors, and some FPGA-based embedded systems support fabrics with dynamic partial reconfiguration (DPR) capability. As a result, traditional hardware/software (HW/SW) partitioning algorithms are no longer suitable. We propose a new MILP (Mixed Integer Linear Programming) formulation to deal with HW/SW partitioning targeting MPSOC (Multi-core Processor System on Chip) with a DPR fabric. Moreover, to help explore the solution space of large scale problems, we propose a method which integrates a heuristic method and an MILP formulation. The experiments show that our approach converges quickly so that results with good quality can be achieved in a reasonable amount of time.

Through-silicon-via (TSV) could provide vertical connections among different dies in 3-D integrated circuits (3-D ICs), but the significant silicon area occupied by TSVs may bring great challenge to designers in 3-D clock tree synthesis (CTS), because only a few whitespace blocks can be used for clock TSV insertion after floorplan and placement are determined, specifically in the area-efficient 3-D IC designs. This paper proposes a whitespace-aware TSV arrangement algorithm in 3-D CTS, which mainly consists of three stages: sink preclustering, whitespace-aware 3-D method of means and medians (3-D-MMMs) topology generation, and deferred-merge embedding merging segment reconstruction. By leveraging the TSV-to-TSV coupling model, we also propose an efficient clock TSV arrangement method to alleviate the coupling effect of adjacent TSVs. Compared with the traditional 3-D-MMM-based CTS with TSV moving adjustment, the experimental results show that our proposed algorithm is more practical and efficient, achieving 49.2% reduction on the average skew and 1.9% reduction on the average power.

As different tiers are stacked together in 3-D integrated circuits, the power/ground (P/G) network simulation becomes more challenging than that of 2-D cases. In this brief, we propose a hierarchical simulation method suitable for 3-D P/G network (HS3-DPG), which takes advantage of the inherent hierarchical structure of 3-D P/G network. The port equivalent model (PEM) is introduced to mask the details of P/G grid in each tier. Besides, we introduce the locality property to further simplify the simulation. Some 3-D P/G network benchmarks extracted from industrial designs are used to verify the correctness of our method. Experimental results show that, HS3-DPG can achieve considerable speedup, while maintaining high accuracy. Simplified PEMs considering the locality property can save nearly 80% memory allocation compared with the full PEMs when the number of through-silicon-vias between the adjacent tiers becomes quite large.

FPGA-based acceleration of matrix operations is a promising solution in mobile systems. However, most related work focuses on a certain operation instead of a complete system. In this paper, we explore the possibility of integrating multiple matrix accelerators with a master processor and propose a universal floating-point matrix processor. The processor supports multiple matrix-matrix operations (Level 3 BLAS) and the matrix size is unlimited. The key component of the processor is a shared matrix cache which enables on-chip communication between different accelerators. This structure reduces the external memory bandwidth requirement and improves the overall performance. Considering the performance of the whole system, an asynchronous instruction execution mechanism is further proposed in the hardware-software interface so as to reduce the workload of the master processor. We demonstrate the system using a DE3 develop board and achieve a computing performance of about 19 GFLOPS. Experiments show the proposed processor achieves higher performance and energy efficiency than some state-of-the-art embedded processors including ARM cortex A9 and NIOS Il/f soft-core processor. The performance of the processor is even comparable to some desktop processors.

With dynamic partial reconfigurable (DPR) capability, an FPGA fabric is no longer static; some of its regions can be dynamically reused for different tasks. Hence current software/hardware (HW/SW) partitioning approaches are no longer applicable to such reconfigurable hardware. This paper incorporates reconfiguration optimization into HW/SW partitioning targeting advanced region-based DPR design flow. Instead of analyzing the tasks for each time step, we introduce a new task graph representation with additional reconfiguration nodes so that the HW/SW partitioning for region-based DPR designs can be optimally solved efficiently by a novel mixed-integer linear programming (MILP) formulation. Experimental results show that our approach can obtain the optimal solutions 10 times faster than the current time-step based approach. For large designs which cannot be handled by the current approaches, our approach can achieve the optimum efficiently in reasonable runtime.

With the miniaturization of electronic devices, small-size but high-capacity power supply systems appear to be more and more important. A hybrid power source, which consists of a fuel cell (FC) and a rechargeable battery, has the advantages of long lifetime and good load-following capabilities. In this article, we propose the schematic of a hybrid power supply system that can be integrated on a chip compatible with present CMOS processes. For the on-chip, fuel-cell-based hybrid power system in wireless sensor node design, we propose a two steps optimization: (1) dynamic power management (DPM), and (2) adaptive fuel cell optimal power point tracking (AOPPT). Simulation results demonstrate that the on-chip FC-Bat hybrid power system can be used for wireless sensor nodes under different usage scenarios. Our proposed DPM method can achieve 12.9% more energy savings than the method without DPM. Meanwhile, implementing our AOPPT approach can save about 17% energy compared with the fixed architecture for the fuel cell system. For an on-chip power system with 1cm 2 area consumption, the wafer-level battery can power a typical sensor node for only about five months, while our on-chip hybrid power system will supply the same sensor node for two years steadily.

As different chips are stacked together in 3D ICs, the power/ground (P/G) network simulation becomes more challenging than that of 2D cases. In this paper, we propose a hierarchical simulation method suitable for 3D P/G network (HS3DPG), which can ensure full parallelism and good scalability with the number of tiers. In the IR drop analysis, when there are 9 tiers, the hierarchical method can be 6.5 times faster than the direct full network simulation. The accuracy of HS3DPG has been verified by a 3D P/G network from the industrial design. Besides, we introduce the “locality” property into HS3DPG to further simplify the simulation. Finally, HS3DPG is used to analyze the voltage distribution of a 3D P/G network with clustered TSVs.

The application specific instruction-set processor (ASIP) offers better computing performance and efficiency by exploiting a set of specific custom instructions (CI) in the processor. However, traditional approaches suffer from the problem that it costs so much computational resource to enumerate and select the optimal custom instructions. In this paper, instead of generating the custom instructions by enumerating all sub-graphs in the data flow graph, we propose a novel custom instruction generation algorithm based on analyzing the basic blocks (BB) which are the smallest execution units of the program. On the basis of characterizing the logic information and structure of basic blocks, both the identification and selection processes could be more efficient by focusing on the feasible candidates with better benefits. A Maximal Weight Independent Set-based formulation is set up to select the final custom instructions based on the efficient identification of candidate custom instructions with logic information of BBs. The experimental result shows that our algorithm can identify 55% more feasible CIs compared with the previous approach. With efficient identification process, we can finally get better CI designs with about 3.27X performance gain of the whole system.

Control and Data Flow Graph (CDFG) is a universal description of program behavior, which is widely used in the co-design of software and hardware. The derivation of CDFG has been done mostly by manually or automatically analyzing corresponding source code, which makes this process time-consuming, error-prone and incomplete. In this paper, we proposed an automated design flow based on runtime instrumentation to generate Enhanced CDFG (ECDFG) with additional runtime information. Though the approach of runtime instrumentation is widely used in software debugging to analyze the program with the accurate runtime information, it is rarely used in software and hardware co-design due to the huge trace data and processing overhead. To overcome the bottle neck of the runtime instrumentation approach, Parallel Background Event Logger is proposed to compress and save the huge amount of trace data. Hierarchical loop structures are detected by intersecting reachable set and backward reachable set. Precise data dependency information is deducted by an address based analytical method named Shower Line Algorithm. With these algorithms and techniques, a set of automatic design tools are implemented to collect runtime events, identify nested and implicit loops and deduct data dependance between modules. Exemplar results demonstrated that Enhanced CDFGs for various programs can be generated correctly with acceptable overhead.

Due to the high integration on vertical stacked layers, power/ground network design becomes one of the critical challenges in 3D IC design. With the leakage-thermal dependency, the increasing on-chip temperature in 3D designs has serious impact on IR drop due to the increased wire resistance and increased leakage current. Power/ground (P/G) TSVs can help to relieve the IR drop violation by vertically connecting the on-chip P/G networks on different layers. However, most previous work only fulfills a margin of the full potential of PG TSVs planning since the P/G grids are restricted in a uniform topology. Besides, the overlook of resistance variation and leakage current will make the results less accurate. In this paper, we present an efficient thermal-aware P/G TSVs planning algorithm based on a sensitivity model with temperature-dependent leakage current considered. The proposed method can overcome the limitation of uniform P/G grid topology and make full use of P/G TSVs planning for the optimization of P/G network by allowing short wires to connect the P/G TSVs to P/G grids in non-uniform topology. Moreover, with resistance variation and increased leakage current caused by high temperature in 3D ICs, more accurate result can be obtained. Both the theoretical analysis and experimental results show the efficiency of our approach. Results show that neglecting thermal impacts on power delivery can underestimate IR drop by about 11%. To relieve the severe IR drop violation, 51.8% more P/G TSVs are needed than the cases without thermal impacts considered. Results also show that our P/G TSV planning based on the sensitivity model can reduce max IR drop by 42.3% and reduce the number of violated nodes by 82.4%.

Dynamic Partial Reconfiguration (DPR) on FPGAs has attracted significant research interests in recent years since it provides benefits such as reduced area and flexible functionality. However, due to the lack of supporting synthesis tools in current DPR design flow, leveraging these benefits requires specific designer expertise with laborious manual design effort. Considering the complicated concurrency relations among functions, it is challenging to properly select Partial Reconfiguration Modules (PR Modules) and partition them into groups so that the hardware modules can be swapped in and out during the run time. What's more, the design of PR Modules also impacts reconfiguration latency and resource utilization greatly. In this paper, we formulate the PR Module generation problem into a standard Maximum-Weight Independent Set Problem (MWISP) so that the original manual exploration can be solved optimally and automatically. Our proposed algorithm not only supports various design constraints, but also has the ability to consider multiple objectives such as area and reconfiguration delay. Experimental results show that our approach can optimize resource utilization and reduce reconfiguration delay with good scalability. Especially, the implementation of the real design case shows that our approach can be embedded in the Xilinx's DPR design flow successfully and it can save around 70% reconfiguration latency overhead compared with the heuristic PR Module generation approaches.

As technology scales, negative bias temperature instability (NBTI) has become a major reliability concern for circuit designers. And the growing process variations can no longer be ignored. Meanwhile, reducing power consumption remains to be one of the design goals. In this paper, a variation-aware supply voltage assignment (SVA) technique combining dual$V_{dd}$assignment and dynamic$V_{dd}$scaling is proposed on a statistical platform, to minimize circuit power under an aging-aware timing constraint. The experimental results show that our SVA technique can mitigate on average 62% of the NBTI-induced circuit delay degradation. Compared with guard-banding and single$V_{dd}$scaling approaches, our approach saves more energy.

With the miniaturization of electronic devices, small size but high capacity power supply system appears to be more and more important. A hybrid power source, which consists of a fuel cell (FC) and a rechargeable battery, has the advantages of long lifetime and good load following capabilities. In this paper, we propose the schematic of a hybrid power supply system, that can be integrated on a chip compatible with present CMOS process. Besides, considering the problem of maximizing the on-chip fuel cell's lifetime, we propose a modified dynamic power management (DPM) algorithm for on-chip fuel cell based hybrid power system in wireless sensor node design. Taking the wireless sensor node powered by this hybrid power system as an example, we analyze the improvement of the FC-Bat hybrid power system. The simulation results demonstrate that the on-chip FC-Bat hybrid power system can be used for wireless sensor node under different usage scenarios. Meanwhile, for an on-chip power system with 1cm2area consumption, the wafer-level battery can power a typical sensor node for only about 5 months, while our on-chip hybrid power system will supply the same sensor node for 2 years steadily.

Due to the increased power density and lower thermal conductivity, 3D is faced with heat dissipation and temperature problem seriously. Previous researches show that leakage power and delay are both relevant to temperature. The timing-power-temperature dependence will potentially negate the performance improvement of 3D designs. TSV (Through-Silicon-Vias) has been shown as an effective way to help heat removal, but they create routing congestions. Therefore, how to reach the trade-off between temperature, via number and delay is required to be solved. Different from previous works on TSV planning which ignored the effects of leakage power, in this paper, we integrate temperature-leakage-timing dependence into thermal via planning of 3D ICs. A weighted via insertion approach, considering both performance and heat dissipation with resource constraint, is proposed to achieve the best balance among delay, via number and temperature. Experiment results show that, with leakage power and resource constraint considered the temperature and via number required can be quite different, and weighted TSV insertion approach can improve thermal via number, by about 5.6%.

Low power design has become one of the most significant requirements when CMOS technology entered the nanometer era. Therefore, timing budget is often performed to slow down as many components as possible so that timing slacks can be applied to reduce the power consumption while maintaining the performance of the whole design. Retiming is a procedure that involves the relocation of flip-flops (FFs) across logic gates to achieve faster clocking speed. In this paper we show that the retiming and slack budgeting problem can be formulated to a convex cost dual network flow problem. Both the theoretical analysis and experimental results show the efficiency of our approach which can not only reduce power consumption by 8.9%, but also speedup previous work by 500 times.

Since most System-on-Chips (SoCs) consist of heterogeneous IP core(s), application-specific Network on Chip (NoC) architectures are appropriate to meet the design requirements. The energy and performance optimization in the NoC design will continue to be the main design goal in nanoscale technologies. In this paper, we present a new hierarchal partitioning approach considering not only the reduction of wire length among cores, but also the optimization of switching power consumption subject to performance constraints. The experimental results on different benchmarks showed that our NoC topology synthesis algorithm can effectively save power and improve performance.

As technology advances, the voltage (IR) drop in the Power/Ground (P/G) network becomes a serious problem in modern IC design. The P/G network co-design with floorplan can improve the power design quality. Different with traditional approaches which analyze P/G network during the floorplanning iterations, in this paper, an efficient pattern selection method is used to provide gradient information for fast signal-integrity estimation. We also propose a novel P/G aware incremental algorithm which can intelligently fix the violations during the floorplanning process. The P/G pin assignment and wire sizing method are adopted during the floorplanning process so that the power routing resource can be minimized with the constraints of IR drop and electron migration (EM) considered. Experimental results based on the MCNC benchmarks show that our design not only significantly speeds up the optimization process, but also optimizes the power routing resource while the quality of the floorplanning is maintained.

With the challenges of growing functionality and scaling chip size, the possible performance improvements should be considered in the earlier IC design stages, which gives more freedom to the later optimization. Potential slack as an effective metric of possible performance improvements is considered in this work which, as far as we known, is the first work that maximizes the potential slack by retiming for synchronous sequential circuit. A simultaneous slack budgeting and incremental retiming algorithm is proposed for maximizing potential slack. The overall slack budget is optimized by relocating the FFs iteratively with the MIS-based slack estimation. Compared with the potential slack of a well-known min-period retiming, our algorithm improves potential slack averagely 19.6% without degrading the circuit performance in reasonable runtime. Furthermore, at the expense of a small amount of timing performance, 0.52% and 2.08%, the potential slack is increased averagely by 19.89% and 28.16% separately, which give a hint of the tradeoff between the timing performance and the slack budget.

Thermal issue is a critical challenge in 3D IC design. To eliminate hotspots, physical layouts are always adjusted by shifting or duplicating hot blocks. However, these modifications may degrade the packing area as well as interconnect distribution greatly. In this paper, we propose some novel thermal-aware incremental changes to optimize these multiple objectives including thermal issue in 3D ICs. Furthermore, to avoid random incremental modification, which may be inefficient and need long runtime to converge, here potential gain is modeled for each candidate incremental change. Based on the potential gain, a novel thermal optimization flow to intelligently choose the best incremental operation is presented. We distinguish the thermal-aware incremental changes in three different categories: migrating computation, growing unit and moving hotspot. Mixed integer linear programming (MILP) models are devised according to these different incremental changes. Experimental results show that migrating computation, growing unit and moving hotspot can reduce max on-chip temperature by 7%, 13% and 15% respectively on MCNC/GSRC benchmarks. Still, experimental results also show that the thermal optimization flow can reduce max on-chip temperature by 14% compared to an existing 3D floorplan tool CBA, and achieve better area and total wirelength improvement than individual operations do.

Abstract—As technology scales, negative bias temperature instability (NBTI) has become a major reliability concern for circuit designers. And the growing process variations can no longer be ignored. Meanwhile, reducing power consumption remains to be one of the design goals. In this paper, a variation-aware supply voltage assignment (SVA) technique combining dual assignment and dynamic scaling is proposed on a statistical platform, to minimize circuit power under an aging-aware timing constraint. The experimental results show that our SVA technique can mitigate on average 62 % of the NBTI-induced circuit delay degrada-tion. Compared with guard-banding and single scaling approaches, our approach saves more energy. Index Terms—Dynamic power, leakage power, negative bias temperature instability (NBTI), supply voltage assignment (SVA). I.

Thermal issue is a critical challenge in 3D IC circuit design. Incorporating thermal vias into 3D IC is a promising way to mitigate thermal issues by lowering down the thermal resistances between device layers. However, it is usually difficult to get enough space at target regions to insert thermal vias. In this paper, we propose a novel analytical algorithm to re-allocate white space for 3D ICs to facilitate via insertion. Experimental results show that after reallocating whitespaces, thermal vias and total wirelength could be reduced by 14% and by 2%, respectively. It also shows that whitespace distribution with via planning alone will degrade performance by 9% while performance-aware via planning method can reduce thermal via number by 60% and the performance is kept nearly unchanged.

In this article we propose techniques that enable efficient exploration of the 3D design space, where each logical block can span more than one silicon layer. Fine-grain 3D integration provides reduced intrablock wire delay as well as improved power consumption. However, the corresponding power and performance advantage is usually underutilized, since various implementations of multilayer blocks require novel physical design and microarchitecture infrastructure to explore 3D microarchitecture design space. We develop a cubic packing engine which can simultaneously optimize physical and architectural design for efficient vertical integration. This technique selects the individual unit designs from a set of single-layer or multilayer implementations to get the best microarchitectural design in terms of performance, temperature, or both. Our experimental results using a design driver of a high-performance superscalar processor show a 36% performance improvement over traditional 2D for 2--4 layers and 14% over 3D with single-layer unit implementations. Since thermal characteristics of 3D integrated circuits are among the main challenges, thermal-aware floorplanning and thermal via insertion techniques are employed to keep the peak temperatures below threshold.

In the context of SOI, thermal constraint is more serious for analog devices. Besides the hot-spot effect, the temperature gradient on symmetrical devices may cause errors and even failures in the function. In order to handle these problems, this paper introduces an accurate thermal model into the placement process. Based on the geometric symmetry which is achieved with corner block list (CBL) for the first time, the thermal model helps to find the thermal-optimal placement. And the experimental results show this method is promising.

For modern processor designs in nanometer technologies, both block and interconnect pipelining are needed to achieve multi-gigahertz clock frequency, but previous approaches consider block pipelining and interconnect pipelining separately. For example, all recent works on wire pipelining assume pre-pipelined components and consider only inserting pipeline stages on point-to-point wire or bus connections. To the best of our knowledge, this paper is the first that considers block pipelining and interconnect pipelining simultaneously. We optimize multiple critical paths or loops in the micro-architecture and insert the pipelines stages optimally in the blocks and wires of these loops to meet the clock frequency requirement. We propose two approaches to this problem. The first approach is based on mixed integer linear programming (MILP) which is theoretically guaranteed to produce the optimal solution, and the second one is an efficient graph-based algorithm that produces near-optimal solutions. Experimental results show that simultaneous block and interconnect pipelining leads to more than 20% improvement over wire-pipelining alone on the overall processor performance. Moreover, the graph-based approach gives solutions very close to the MILP results ( 2% more than MILP results on average) but in a much shorter runtime.

Leakage power is becoming a key design challenge in current and future CMOS designs. Due to technology scaling, the leakage power is rising so quickly that it largely elevates the die temperature. In this paper, we deeply investigate the impact of leakage power on thermal profile in 2D and 3D floorplanning. Our results show that chip temperature can increase by about 11 V in 2D design and 68 V for 3D case with leakage power considered. Then we propose a thermal-driven floorplanning flow integrated with an iterative leakage-aware thermal analysis process to optimize chip temperature and save leakage power consumption. Experimental results show that for 2D design, the max chip temperature can be reduced by about 8 "C and the proportion of leakage power to total power can be reduced from 19.17% to 11.12%. The corresponding results for 3D are 60 degC temperature reduction and 16.3% less leakage power proportion.

More and more IP cores are used in modern SOC designing. In order to place IP cores effectively, hierarchical design has been introduced and better supported by fixed-outline floorplanning than outline-free [1]. In this paper, we also consider buffer insertion issue in fixed-outline floorplanning with the help of the Less Flexibility First (LFF) algorithm, which runs in a fixed-outline area and places IP cores as hard modules one after another with no backtracks. Unlike Simulated Annealing (SA), LFF is a deterministic packing algorithm and runs without topological representations. Therefore, it is able to tell the difference among geometric floorplans with the same topological structure, which is helpful to get a better result for buffer planning since buffer insertions are quite sensitive to a geometric change. Moreover, a 2-staged packing and a post greedy method after packing are also introduced based on a net-classing strategy and finally help to achieve great success rate improvement of buffer insertion (about +40.7% in 0.18um and +37.1% in 0.07μm). Meanwhile, our buffer planning method runs much faster than SA, since it is deterministic and has no backtracks. Besides, it is also useful to provide an initial solution for SA for further optimization.

Thermal issues are a primary concern in the threedimensional (3D) integrated circuit (IC) design. Temperature, area, and wire length must be simultaneously optimized during 3D floorplanning, significantly increasing optimization complexity. Most existing floorplanners use combinatorial stochastic optimization techniques, hampering performance and scalability when used for 3D floorplanning. In this work, we propose and evaluate a scalable, temperature-aware, force-directed floorplanner called 3D-STAF. Force-directed techniques, although efficient at reacting to physical information such as temperature gradients, must eventually eliminate overlap. This can cause significant displacement when used for heterogeneous blocks. To smooth the transition from an unconstrained 3D placement to a legalized, layer-assigned floorplan, we propose a three-stage force-directed optimization flow combined with new legalization techniques that eliminate white spaces and block overlapping during multi-layer floorplanning. A temperature-dependent leakage model is used within 3D-STAF to permit optimization based on the feedback loop connecting thermal profile and leakage power consumption. 3D-STAF has good performance that scales well for large problem instances. Compared to recently published 3D floorplanning work, 3D-STAF improves the area by 6%, wire length by 16%, via count by 22%, peak temperature by 6% while running nearly 4× faster on average.

Most previous 3D IC research focused on "stacking" traditional 2D silicon layers, so the interconnect reduction is limited to interblock delays. In this paper, we propose techniques that enable efficient exploration of the 3D design space where each logical block can span more than one silicon layers. Although further power and performance improvement is achievable through fine grain 3D integration, the necessary modeling and tool infrastructure has been mostly missing. We develop a cube packing engine which can simultaneously optimize physical and architectural design for effective utilization of 3D in terms of performance, area and temperature. Our experimental results using a design driver show 36% performance improvement (in BIPS) over 2D and 14% over 3D with single layer blocks. Additionally multi-layer blocks can provide up to 30% reduction in power dissipation compared to the single-layer alternatives. Peak temperature of the design is kept within limits as a result of thermal-aware floorplanning and thermal via insertion techniques.

3D packing is a fundamental problem for VLSI design. It arises from 3D-ICs floorplan design and task schedule in reconfigurable FPGA design. In this paper, we present a novel 3D floorplan representation by improving the 3D bounded slice-surface grid (3D-BSG) structure in two aspects: (1) optimize the evaluation time complexity from O(n3) to O(n2) by using three block relation graphs; (2) handle the infeasible assignment problem of 3D-BSG in linear time by giving the rule of null relation rooms. The effectiveness and efficiency of the fast 3D-BSG are shown by both theoretical analysis and experimental results. The average speedup compared to the original 3D-BSG is 44times high.

Although the emerging 3D integration technology can significantly reduce interconnect delay, chip area, and power dissipation in nanometer technologies, its impact on overall system performance is still poorly understood due to the lack of tools and systematic flows to evaluate 3D microarchitectural designs. The contribution of this paper is the development of MEVA-3D, an automated physical design and architecture performance estimation flow for 3D architectural evaluation which includes 3D floorplanning, routing, interconnect pipelining and automated thermal via insertion, and associated die size, performance, and thermal modeling capabilities. We apply this flow to a simple, out-of-order superscalar microprocessor to evaluate the performance and thermal behavior in 2D and 3D designs, and demonstrate the value of MEVA-3D in providing quantitative evaluation results to guide 3D architecture designs. In particular, we show that it is feasible to manage thermal challenges with a combination of thermal vias and double-sided heat sinks, and report modest system performance gains in 3D designs for these simple test examples.

The dominating contribution of interconnect to system performance has made it critical to plan the resources of the buffers and routes in the early stage of the layout. In this paper, we integrate floorplanning with buffer insertion for performance-driven design processes. We devise a two-step method to evaluate the feasible buffer insertion sites, which can improve the efficiency of the buffer-planning algorithm. By partitioning all empty spaces into blocks in the packing process, the buffer allocation is handled as an integral part of the floorplanning. Our buffer-planning algorithm maps the buffers into tiles with consideration of routing congestion. In this approach, we construct a distribution graph to model the possible routes. The buffer allocation method is performed on the updated distribution graph to find the buffer locations with their respective congestion costs. The method is based on a simulated annealing approach, which is composed of multiple phases to speed up the optimization. Since there is more freedom with floorplan optimization, the empirical results demonstrate better performance.

Corner Block List (CBL) was recently proposed as an efficient representation for MOSAIC packing of rectangles. Although the original method is really innovative, there still remains room for improvement for our purpose. This article proposes a compact algorithm for placement based on corner block list. By introducing the dummy blocks in CBL, our algorithm can intellectively employ dummy blocks in the packing to represent the placement including empty rooms, which corner block list cannot represent. Our algorithm can obtain the fast convergence to an optimal solution. Based on the compact approach, we propose a new way to handle arbitrary shaped rectilinear modules. The experimental results are demonstrated by some benchmark data and the performance shows effectiveness of the proposed method.

This paper studies the buffer planning problem for interconnect-centric floorplanning for nanometer technologies. The dead-spaces are the spaces within a placement that are not held by any circuit block. In this paper, we proposed a buffer planning algorithm based on dead space redistribution to make good use of dead-spaces for buffer insertion. Associated with circuit blocks under topological representations, the dead space can be redistributed by freely moving some circuit blocks within their rooms in the placement. The total area and the topology of the placement keep unchanged while doing the dead space redistribution. The number of nets satisfying the delay constraint can be increased by redistributing the dead space all over the placement, which has been demonstrated by the experimental results. The increment of the number of nets that satisfy delay constraints is 9% on an average.

By dividing the packing area into routing tiles, we can give the budget of the buffer insertion. And the detail locating of the blocks in their rooms can be implemented for each iterations during the annealing process to favor the later buffer planning. The buffer insertion will affect the possible routes as well the congestion of the packing. The congestion estimation in this paper takes the buffer insertion into account. So we devise a buffer planning algorithm to allocate the buffer into tiles with congestion information considered. The buffer allocation problem is formulated into a net flow problem and the buffer allocation can be handled as an integral part in the floorplanning process. Since there is more freedom for floorplan optimization, the floorplanning algorithm integrated with buffer planning can result in better performance and chip area.

Previous works on buffer planning are mainly based on fixed die placement. It is necessary to reduce the complexity of computing the feasible buffer insertion sites to integrate the buffer planning with the floorplanning process. In this paper, we give an efficient buffer planning algorithm with linear complexity by computing all the feasible buffer insertion sites in a 2-step method. By partitioning all the dead spaces into blocks while doing the packing, the buffer allocation can be handled as an integral part in the floorplanning process. Our method is based on a simulated annealing approach which is divided into two phases: timing optimization phase and buffer insertion phase. Since there is more freedom for floorplan optimization, the floorplanning algorithm integrated with buffer planning can result in better time performance and chip area.

In floorplanning of typical VLSI design, some modules are required to satisfy some placement constraints in the final packing. Boudary Constraint is one kind of those placement constraints to pack some modules along one of the four sides: on the left, on the right, at the bottom or at the top of the final floorplan. We implement the boundary constraint algorithm for general floorplan by extending the Corner Block List (CBL) - a new efficient topology representation for non-slicing floorplan. Our contribution is to find the necessary and sufficient characterization of the modules along the boundary represented by Corner Block List. So that we can check the boundary constraints by scanning the intermediate solutions in the linear time during the simulated annealing process and fix the corner block list in case the constraints are violated. The experiment results are demonstrated by several examples of MCNC benchmarks and the performance is remarkable.

The abutment constraint problem is one of the common constraints in practice to favor the transmission of data between blocks. Based on Corner Block List(CBL), a new algorithm to deal with abutment constraints is developed in this paper. We can obtain the abutment information by scanning the intermediate solutions represented by CBL in linear time during the simulated annealing process and fix the CBL in case the constraints are violated. Based on this algorithm, a new method to deal with L-shaped/T-shaped blocks is proposed. The shape flexibility of the soft blocks and the rotation and reflection of L-shaped/T-shaped blocks are exploited to obtain a tight packing. The experiment results are demonstrated by some benchmark data and the performance shows effectiveness of the proposed method.