The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

The paper surveys a decade of R&D on coarse grain reconfigurable hardware and related CAD, points out why this emerging discipline is heading toward a dichotomy of computing science, and advocates the introduction of a new soft machine paradigm to replace CAD by compilation.

A decade of reconfigurable computing: a visionary retrospective

The coarse-grained reconfigurable architectures have advantages over the traditional FPGAs in terms of delay, area and configuration time. To execute entire applications, most of them combine an instruction set processor(ISP) and a reconfigurable matrix. However, not much attention is paid to the integration of these two parts, which results in high communication overhead and programming difficulty. To address this problem, we propose a novel architecture with tightly coupled very long instruction word (VLIW) processor and coarse-grained reconfigurable matrix. The advantages include simplified programming model, shared resource costs, and reduced communication overhead. To exploit this architecture, our previously developed compiler framework is adapted to the new architecture. The results show that the new architecture has good performance and is very compiler-friendly.

ADRES: An Architecture with Tightly Coupled VLIW Processor and Coarse-Grained Reconfigurable Matrix

The main characteristic of Reconfigurable Computing is the presence of hardware that can be reconfigured to implement specific functionality more suitable for specially tailored hardware than on a simple uniprocessor. Reconfigurable computing systems join microprocessors and programmable hardware in order to take advantage of the combined strengths of hardware and software and have been used in applications ranging from embedded systems to high performance computing. Many of the fundamental theories have been identified and used by the Hardware/Software Co-Design research field. Although the same background ideas are shared in both areas, they have different goals and use different approaches.This book is intended as an introduction to the entire range of issues important to reconfigurable computing, using FPGAs as the context, or "computing vehicles" to implement this powerful technology. It will take a reader with a background in the basics of digital design and software programming and provide them with the knowledge needed to be an effective designer or researcher in this rapidly evolving field.

· Treatment of FPGAs as computing vehicles rather than glue-logic or ASIC substitutes
· Views of FPGA programming beyond Verilog/VHDL
· Broad set of case studies demonstrating how to use FPGAs in novel and efficient ways

Reconfigurable Computing: The Theory and Practice of FPGA-Based Computation

The high accuracy of deep neural networks (NNs) has led to the development of NN accelerators that improve performance by two orders of magnitude. However, scaling these accelerators for higher performance with increasingly larger NNs exacerbates the cost and energy overheads of their memory systems, including the on-chip SRAM buffers and the off-chip DRAM channels.This paper presents the hardware architecture and software scheduling and partitioning techniques for TETRIS, a scalable NN accelerator using 3D memory. First, we show that the high throughput and low energy characteristics of 3D memory allow us to rebalance the NN accelerator design, using more area for processing elements and less area for SRAM buffers. Second, we move portions of the NN computations close to the DRAM banks to decrease bandwidth pressure and increase performance and energy efficiency. Third, we show that despite the use of small SRAM buffers, the presence of 3D memory simplifies dataflow scheduling for NN computations. We present an analytical scheduling scheme that matches the efficiency of schedules derived through exhaustive search. Finally, we develop a hybrid partitioning scheme that parallelizes the NN computations over multiple accelerators. Overall, we show that TETRIS improves mthe performance by 4.1x and reduces the energy by 1.5x over NN accelerators with conventional, low-power DRAM memory systems.

https://dl.acm.org/doi/pdf/10.1145/3037697.3037702

TETRIS: Scalable and Efficient Neural Network Acceleration with 3D Memory

This paper introduces MorphoSys, a reconfigurable computing system developed to investigate the effectiveness of combining reconfigurable hardware with general-purpose processors for word-level, computation-intensive applications. MorphoSys is a coarse-grain, integrated, and reconfigurable system-on-chip, targeted at high-throughput and data-parallel applications. It is comprised of a reconfigurable array of processing cells, a modified RISC processor core, and an efficient memory interface unit. This paper describes the MorphoSys architecture, including the reconfigurable processor array, the control processor, and data and configuration memories. The suitability of MorphoSys for the target application domain is then illustrated with examples such as video compression, data encryption and target recognition. Performance evaluation of these applications indicates improvements of up to an order of magnitude (or more) on MorphoSys, in comparison with other systems.

MorphoSys: an integrated reconfigurable system for data-parallel and computation-intensive applications

In this paper, we describe the implementation of MorphoSys, a reconfigurable processing system targeted at data-parallel and computation-intensive applications. The MorphoSys architecture consists of a reconfigurable component (an array of reconfigurable cells) combined with a RISC control processor and a high bandwidth memory interface. We briefly discuss the system-level model, array architecture, and control processor. Next, we present the detailed design implementation and the various aspects of physical layout of different sub-blocks of MorphoSys. The physical layout was constrained for 100 MHz operation, with low power consumption, and was implemented using 0.35 μm, four metal layer CMOS (3.3 Volts) technology. We provide simulation results for the MorphoSys architecture (based on VHDL model) for some typical data-parallel applications (video compression and automatic target recognition). The results indicate that the MorphoSys system can achieve significantly better performance for most of these applications in comparison with other systems and processors.

Design and Implementation of the MorphoSys Reconfigurable ComputingProcessor

Dynamically reconfigurable architectures are emerging as a viable design alternative to implement a wide range of computationally intensive applications. At the same time, an urgent necessity has arisen for support tool development to automate the design process and achieve optimal exploitation of the architectural features of the system. Task scheduling and context (configuration) management become very critical issues in achieving the high performance that digital signal processing (DSP) and multimedia applications demand. This article proposes a strategy to automate the design process which considers all possible optimizations that can be carried out at compilation time, regarding context and data transfers. This strategy is general in nature and could be applied to different reconfigurable systems. We also discuss the key aspects of the scheduling problem in a reconfigurable architecture such as MorphoSys. In particular, we focus on a task scheduling methodology for DSP and multimedia applications, as well as the context management and scheduling optimizations.

A framework for reconfigurable computing: task scheduling and context management

This paper introduces MorphoSys, a parallel system-on-chip which combines a RISC processor with an array of coarse-grain reconfigurable cells. MorphoSys integrates the flexibility of general-purpose systems and high performance levels typical of application-specific systems. Simulation results presented here show significant performance enhancements for different classes of applications, as compared to conventional architectures.

/pdf/the-morphosys-parallel-reconfigurable-system-ctgwljkb5m.pdf

The MorphoSys Parallel Reconfigurable System

In this paper, we present a case study for the design, programming and usage of a reconfigurable system-on-chip, MorphoSys, which is targeted at computation-intensive applications. This 2-million transistor design combines a reconfigurable array of cells with a RISC processor core and a high bandwidth memory interface. The system architecture, software tools including a scheduler for reconfigurable systems, and performance analysis (with impressive speedups) for target applications are described.

/pdf/morphosys-case-study-of-a-reconfigurable-computing-system-38upv9i4b9.pdf

H. Singh

Papers

MorphoSys: an integrated reconfigurable system for data-parallel and computation-intensive applications

Design and Implementation of the MorphoSys Reconfigurable ComputingProcessor

A framework for reconfigurable computing: task scheduling and context management

The MorphoSys Parallel Reconfigurable System

MorphoSys: case study of a reconfigurable computing system targeting multimedia applications