To facilitate the development of future FPGA architectures and CAD tools -- both embedded programmable fabrics and pure-play FPGAs -- there is a need for a large scale, publicly available software suite that can synthesize circuits into easily-described hypothetical FPGA architectures. These circuits should be captured at the HDL level, or higher, and pass through logical and physical synthesis. Such a tool must provide detailed modelling of area, performance and energy to enable architecture exploration. As software flows themselves evolve to permit design capture at ever higher levels of abstraction, this downstream full-implementation flow will always be required. This paper describes the current status and new release of an ongoing effort to create such a flow - the 'Verilog to Routing' (VTR) project, which is a broad collaboration of researchers. There are three core tools: ODIN II for Verilog Elaboration and front-end hard-block synthesis, ABC for logic synthesis, and VPR for physical synthesis and analysis. ODIN II now has a simulation capability to help verify that its output is correct, as well as specialized synthesis at the elaboration step for multipliers and memories. ABC is used to optimize the 'soft' logic of the FPGA. The VPR-based packing, placement and routing is now fully timing-driven (the previous release was not) and includes new capability to target complex logic blocks. In addition we have added a set of four large benchmark circuits to a suite of previously-released Verilog HDL circuits. Finally, we illustrate the use of the new flow by using it to help architect a floating-point unit in an FPGA, and contrast it with a prior, much longer effort that was required to do the same thing.

The VTR project: architecture and CAD for FPGAs from verilog to routing

Cloud computing is becoming a major trend for delivering and accessing infrastructure on demand via the network. Meanwhile, the usage of FPGAs (Field Programmable Gate Arrays) for computation acceleration has made significant inroads into multiple application domains due to their ability to achieve high throughput and predictable latency, while providing programmability, low power consumption and time-to-value. Many types of workloads, e.g. databases, big data analytics, and high performance computing, can be and have been accelerated by FPGAs. As more and more workloads are being deployed in the cloud, it is appropriate to consider how to make FPGAs and their capabilities available in the cloud. However, such integration is non-trivial due to issues related to FPGA resource abstraction and sharing, compatibility with applications and accelerator logics, and security, among others. In this paper, a general framework for integrating FPGAs into the cloud is proposed and a prototype of the framework is implemented based on OpenStack, Linux-KVM and Xilinx FPGAs. The prototype enables isolation between multiple processes in multiple VMs, precise quantitative acceleration resource allocation, and priority-based workload scheduling. Experimental results demonstrate the effectiveness of this prototype, an acceptable overhead, and good scalability when hosting multiple VMs and processes.

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Enabling FPGAs in the cloud

Memristor-based systems and their potential applications, in which memristor is both a nonlinear element and a memory element, have been received significant attention recently. A memristor-based hyperchaotic system with hidden attractor is studied in this paper. The dynamics properties of this hyperchaotic system are discovered through equilibria, Lyapunov exponents, bifurcation diagram, Poincaré map and limit cycles. In addition, its anti-synchronization scheme via adaptive control method is also designed and MATLAB simulations are shown. Finally, an electronic circuit emulating the memristor-based hyperchaotic system has been designed using off-the-shelf components.

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A Memristor-Based Hyperchaotic System with Hidden Attractors: Dynamics, Synchronization and Circuital Emulating

The ReconOS operating system for reconfigurable computing offers a unified multithreaded programming model and OS services for threads executing in software and threads mapped to reconfigurable hardware. The OS interface lets hardware threads interact with software threads using well-known mechanisms such as semaphores, mutexes, condition variables, and message queues. By semantically integrating hardware accelerators into a standard OS environment, ReconOS allows for rapid design-space exploration, supports a structured application development process, and improves the portability of applications between different reconfigurable computing systems.

ReconOS: An Operating System Approach for Reconfigurable Computing

The development of future FPGA fabrics with more sophisticated and complex logic blocks requires a new CAD flow that permits the expression of that complexity and the ability to synthesize to it. In this paper, we present a new logic block description language that can depict complex intra-block interconnect, hierarchy and modes of operation. These features are necessary to support modern and future FPGA complex soft logic blocks, memory and hard blocks. The key part of the CAD flow associated with this complexity is the packer, which takes the logical atomic pieces of the complex blocks and groups them into whole physical entities. We present an area-driven generic packing tool that can pack the logical atoms into any heterogeneous FPGA described in the new language, including many different kinds of soft and hard logic blocks. We gauge its area quality by comparing the results achieved with a lower bound on the number of blocks required, and then illustrate its explorative capability in two ways: on fracturable LUT soft logic architectures, and on hard block memory architectures. The new infrastructure attaches to a flow that begins with a Verilog front-end, permitting the use of benchmarks that are significantly larger than the usual ones, and can target heterogenous FPGAs.

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Architecture description and packing for logic blocks with hierarchy, modes and complex interconnect

This brief presents a reconfigurable VLSI architecture which is designed for multi-transform codec in several video coding standards of MPEG-2/4, VC-1, H.264/AVC and AVS. The reconfigurable multiple constant multiplication algorithm with two fusing strategies is provided to generate constant multipliers in the matrix calculation blocks. Additionally, adder-sharing strategy is adopted in the unified preprocessing/postprocessing block to save circuit areas. The proposed architecture can support different standards through static reconfiguration and forward/inverse transform functions through dynamic reconfiguration. It is suitable for the real-time processing of 1080P HD video codec with six video standards transforms.

A Reconfigurable Multi-Transform VLSI Architecture Supporting Video Codec Design

Partially reconfigurable systems are promising computing platforms for streaming applications, which demand both hardware efficiency and reconfigurable flexibility. To realize the full potential of these systems, a streaming-based partially reconfigurable architecture and unified software/hardware multithreaded programming model (SPREAD) is presented in this paper. SPREAD is a reconfigurable architecture with a unified software/hardware thread interface and high throughput point-to-point streaming structure. It supports dynamic computing resource allocation, runtime software/hardware switching, and streaming-based multithreaded management at the operating system level. SPREAD is designed to provide programmers of streaming applications with a unified view of threads, allowing them to exploit thread, data, and pipeline parallelism; it enhances hardware efficiency while simplifying the development of streaming applications for partially reconfigurable systems. Experimental results targeting cryptography applications demonstrate the feasibility and superior performance of SPREAD. Moreover, the parallelized Advanced Encryption Standard (AES), Data Encryption Standard (DES), and Triple DES (3DES) hardware threads on field-programmable gate arrays show 1.61-4.59 times higher power efficiency than their implementations on state-of-the-art graphics processing units.

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SPREAD: A Streaming-Based Partially Reconfigurable Architecture and Programming Model

A radiation hardened resistive SRAM structure (rSRAM) is proposed for the SRAM-based FPGAs in this paper. The rSRAM extends the conventional 6T SRAM structure by connecting memristors between the information nodes and drains of the transistors which compose cross-coupled invertors. With memristors connected to drains of OFF transistors configured to high resistance state while others configured to low resistance state forming stable voltage dividing path, the rSRAM structure is immune to both multiple-node upsets and multiplebit upsets (MBUs). The simulation result demonstrates that rSRAM cell can tolerate simultaneous disruptions affecting all sensitive nodes with an LET (Liner Energy Transfer) of 100Mev-cm2/mg.

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A novel memristor-based rSRAM structure for multiple-bit upsets immunity

As a promising computing platform for stream processing, partially reconfigurable systems have shown their hardware efficiency and reconfiguration flexibility. This paper presents a partially reconfigurable architecture supporting hardware threads. It gives a unified software/hardware thread interface and high throughput point-to-point streaming structure. Dynamic computing resource allocation and streaming-based multi-threaded management are also provided at operating system level. It is easy for programmers to exploit the inherent thread, data and pipeline parallelism in a unified view of threads, enhancing hardware efficiency while improving productivity. The experimental results on a cryptography application demonstrate the feasibility and superior performance. Moreover, the parallelized AES, DES and 3DES hardware threads on field-programmable gate arrays show 1.61–4.59 times higher power efficiency than their implementations on state-of-the-art graphics processing units.

A partially reconfigurable architecture supporting hardware threads

In this paper, we propose a novel statistical capacitance extraction method for interconnects considering process variations. The new method, called statCap, is based on the spectral stochastic method where orthogonal polynomials are used to represent the statistical processes in a deterministic way. We first show how the variational potential coefficient matrix is represented in a first-order form using Taylor expansion and orthogonal decomposition. Then an augmented potential coefficient matrix, which consists of the coefficients of the polynomials, is derived. After that, corresponding augmented system is solved to obtain the variational capacitance values in the orthogonal polynomial form. Experimental results show that our method is two orders of magnitude faster than the recently proposed statistical capacitance extraction method based on the spectral stochastic collocation approach and many orders of magnitude faster than the Monte Carlo method for several practical interconnect structures.

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Jiarong Tong

Papers

A Reconfigurable Multi-Transform VLSI Architecture Supporting Video Codec Design

SPREAD: A Streaming-Based Partially Reconfigurable Architecture and Programming Model

A novel memristor-based rSRAM structure for multiple-bit upsets immunity

A partially reconfigurable architecture supporting hardware threads

Variational capacitance modeling using orthogonal polynomial method