A Test Bench for Distortion-Energy Optimization of a DSP-Based H.264/SVC Decoder

International audienceThis paper describes an OMAP based real-time test bench to find the Pareto frontier of an H.264/SVC decoder within a distortion-energy optimization space. A metric to estimate video distortion is introduced. In addition, energy consumption estimates are obtained from real-time measurements of the computational load. Finally, test bench operation is successfully demonstrated with different H.264/SVC-compliant sets of sequences

A CAD Tool for Synthesizing Optimized Variants of Altera\u27s Nios II Soft-Core Processor

Soft-core processors offer embedded system designers the benefits of customization, flexibility and reusability. Altera\u27s NIOS II soft-core processor is a popular, commercially available soft-core processor that can be implemented on a variety of Altera FPGAs. In this thesis, the Nios II soft-core processor from Altera Corporation was studied and a VHDL implementation, called UW_Nios II, was developed. UW_Nios II was developed to enable us to perform design space exploration (DSE) for the Nios II processor. It was evaluated and compared with Altera Nios II and shown to be competitive. SCBuild is an existing CAD tool that was developed to enable DSE of soft-core processors. We modified SCBuild to automatically explore the design space of the UW_Nios II using a genetic algorithm. This tool can accurately estimate the area and critical path delay of different variants of the UW_Nios II on a field programmable gate array. Through experiments conducted using SCBuild, it was shown that employing a genetic algorithm to explore the design space of parameterized Nios II core, with a large design space, helps designers find optimized variants of UW_Nios II

3D-SoftChip: A novel 3D vertically integrated adaptive computing system [thesis]

At present, as we enter the nano and giga-scaled integrated-circuit era, there are many system design challenges which must be overcome to resolve problems in current systems. The incredibly increased nonrecurring engineering (NRE) cost, abruptly shortened Time-to- Market (ITA) period and ever widening design productive gaps are good examples illustrating the problems in current systems. To cope with these problems, the concept of an Adaptive Computing System is becoming a critical technology for next generation computing systems. The other big problem is an explosion in the interconnection wire requirements in standard planar technology resulting from the very high data-bandwidth requirements demanded for real-time communications and multimedia signal processing. The concept of 3D-vertical integration of 2D planar chips becomes an attractive solution to combat the ever increasing interconnect wire requirements. As a result, this research proposes the concept of a novel 3D integrated adaptive computing system, which we term 3D-ACSoC. The architecture and advanced system design methodology of the proposed 3D-SoftChip as a forthcoming giga-scaled integrated circuit computing system has been introduced, along with high-level system modeling and functional verification in the early design stage using SystemC

FPGA structures for high speed and low overhead dynamic circuit specialization

A Field Programmable Gate Array (FPGA) is a programmable digital electronic chip. The FPGA does not come with a predefined function from the manufacturer; instead, the developer has to define its function through implementing a digital circuit on the FPGA resources. The functionality of the FPGA can be reprogrammed as desired and hence the name “field programmable”. FPGAs are useful in small volume digital electronic products as the design of a digital custom chip is expensive. Changing the FPGA (also called configuring it) is done by changing the configuration data (in the form of bitstreams) that defines the FPGA functionality. These bitstreams are stored in a memory of the FPGA called configuration memory. The SRAM cells of LookUp Tables (LUTs), Block Random Access Memories (BRAMs) and DSP blocks together form the configuration memory of an FPGA. The configuration data can be modified according to the user’s needs to implement the user-defined hardware. The simplest way to program the configuration memory is to download the bitstreams using a JTAG interface. However, modern techniques such as Partial Reconfiguration (PR) enable us to configure a part in the configuration memory with partial bitstreams during run-time. The reconfiguration is achieved by swapping in partial bitstreams into the configuration memory via a configuration interface called Internal Configuration Access Port (ICAP). The ICAP is a hardware primitive (macro) present in the FPGA used to access the configuration memory internally by an embedded processor. The reconfiguration technique adds flexibility to use specialized ci rcuits that are more compact and more efficient t han t heir b ulky c ounterparts. An example of such an implementation is the use of specialized multipliers instead of big generic multipliers in an FIR implementation with constant coefficients. To specialize these circuits and reconfigure during the run-time, researchers at the HES group proposed the novel technique called parameterized reconfiguration that can be used to efficiently and automatically implement Dynamic Circuit Specialization (DCS) that is built on top of the Partial Reconfiguration method. It uses the run-time reconfiguration technique that is tailored to implement a parameterized design. An application is said to be parameterized if some of its input values change much less frequently than the rest. These inputs are called parameters. Instead of implementing these parameters as regular inputs, in DCS these inputs are implemented as constants, and the application is optimized for the constants. For every change in parameter values, the design is re-optimized (specialized) during run-time and implemented by reconfiguring the optimized design for a new set of parameters. In DCS, the bitstreams of the parameterized design are expressed as Boolean functions of the parameters. For every infrequent change in parameters, a specialized FPGA configuration is generated by evaluating the corresponding Boolean functions, and the FPGA is reconfigured with the specialized configuration. A detailed study of overheads of DCS and providing suitable solutions with appropriate custom FPGA structures is the primary goal of the dissertation. I also suggest different improvements to the FPGA configuration memory architecture. After offering the custom FPGA structures, I investigated the role of DCS on FPGA overlays and the use of custom FPGA structures that help to reduce the overheads of DCS on FPGA overlays. By doing so, I hope I can convince the developer to use DCS (which now comes with minimal costs) in real-world applications. I start the investigations of overheads of DCS by implementing an adaptive FIR filter (using the DCS technique) on three different Xilinx FPGA platforms: Virtex-II Pro, Virtex-5, and Zynq-SoC. The study of how DCS behaves and what is its overhead in the evolution of the three FPGA platforms is the non-trivial basis to discover the costs of DCS. After that, I propose custom FPGA structures (reconfiguration controllers and reconfiguration drivers) to reduce the main overhead (reconfiguration time) of DCS. These structures not only reduce the reconfiguration time but also help curbing the power hungry part of the DCS system. After these chapters, I study the role of DCS on FPGA overlays. I investigate the effect of the proposed FPGA structures on Virtual-Coarse-Grained Reconfigurable Arrays (VCGRAs). I classify the VCGRA implementations into three types: the conventional VCGRA, partially parameterized VCGRA and fully parameterized VCGRA depending upon the level of parameterization. I have designed two variants of VCGRA grids for HPC image processing applications, namely, the MAC grid and Pixie. Finally, I try to tackle the reconfiguration time overhead at the hardware level of the FPGA by customizing the FPGA configuration memory architecture. In this part of my research, I propose to use a parallel memory structure to improve the reconfiguration time of DCS drastically. However, this improvement comes with a significant overhead of hardware resources which will need to be solved in future research on commercial FPGA configuration memory architectures

Interstellar: Using Halide's Scheduling Language to Analyze DNN Accelerators

We show that DNN accelerator micro-architectures and their program mappings represent specific choices of loop order and hardware parallelism for computing the seven nested loops of DNNs, which enables us to create a formal taxonomy of all existing dense DNN accelerators. Surprisingly, the loop transformations needed to create these hardware variants can be precisely and concisely represented by Halide's scheduling language. By modifying the Halide compiler to generate hardware, we create a system that can fairly compare these prior accelerators. As long as proper loop blocking schemes are used, and the hardware can support mapping replicated loops, many different hardware dataflows yield similar energy efficiency with good performance. This is because the loop blocking can ensure that most data references stay on-chip with good locality and the processing units have high resource utilization. How resources are allocated, especially in the memory system, has a large impact on energy and performance. By optimizing hardware resource allocation while keeping throughput constant, we achieve up to 4.2X energy improvement for Convolutional Neural Networks (CNNs), 1.6X and 1.8X improvement for Long Short-Term Memories (LSTMs) and multi-layer perceptrons (MLPs), respectively.Comment: Published as a conference paper at ASPLOS 202

An Scalable matrix computing unit architecture for FPGA and SCUMO user design interface

High dimensional matrix algebra is essential in numerous signal processing and machine learning algorithms. This work describes a scalable square matrix-computing unit designed on the basis of circulant matrices. It optimizes data flow for the computation of any sequence of matrix operations removing the need for data movement for intermediate results, together with the individual matrix operations' performance in direct or transposed form (the transpose matrix operation only requires a data addressing modification). The allowed matrix operations are: matrix-by-matrix addition, subtraction, dot product and multiplication, matrix-by-vector multiplication, and matrix by scalar multiplication. The proposed architecture is fully scalable with the maximum matrix dimension limited by the available resources. In addition, a design environment is also developed, permitting assistance, through a friendly interface, from the customization of the hardware computing unit to the generation of the final synthesizable IP core. For N x N matrices, the architecture requires N ALU-RAM blocks and performs O(N*N), requiring N*N +7 and N +7 clock cycles for matrix-matrix and matrix-vector operations, respectively. For the tested Virtex7 FPGA device, the computation for 500 x 500 matrices allows a maximum clock frequency of 346 MHz, achieving an overall performance of 173 GOPS. This architecture shows higher performance than other state-of-the-art matrix computing units

Hardware Architectures for Post-Quantum Cryptography

The rapid development of quantum computers poses severe threats to many commonly-used cryptographic algorithms that are embedded in different hardware devices to ensure the security and privacy of data and communication. Seeking for new solutions that are potentially resistant against attacks from quantum computers, a new research field called Post-Quantum Cryptography (PQC) has emerged, that is, cryptosystems deployed in classical computers conjectured to be secure against attacks utilizing large-scale quantum computers. In order to secure data during storage or communication, and many other applications in the future, this dissertation focuses on the design, implementation, and evaluation of efficient PQC schemes in hardware. Four PQC algorithms, each from a different family, are studied in this dissertation. The first hardware architecture presented in this dissertation is focused on the code-based scheme Classic McEliece. The research presented in this dissertation is the first that builds the hardware architecture for the Classic McEliece cryptosystem. This research successfully demonstrated that complex code-based PQC algorithm can be run efficiently on hardware. Furthermore, this dissertation shows that implementation of this scheme on hardware can be easily tuned to different configurations by implementing support for flexible choices of security parameters as well as configurable hardware performance parameters. The successful prototype of the Classic McEliece scheme on hardware increased confidence in this scheme, and helped Classic McEliece to get recognized as one of seven finalists in the third round of the NIST PQC standardization process. While Classic McEliece serves as a ready-to-use candidate for many high-end applications, PQC solutions are also needed for low-end embedded devices. Embedded devices play an important role in our daily life. Despite their typically constrained resources, these devices require strong security measures to protect them against cyber attacks. Towards securing this type of devices, the second research presented in this dissertation focuses on the hash-based digital signature scheme XMSS. This research is the first that explores and presents practical hardware based XMSS solution for low-end embedded devices. In the design of XMSS hardware, a heterogenous software-hardware co-design approach was adopted, which combined the flexibility of the soft core with the acceleration from the hard core. The practicability and efficiency of the XMSS software-hardware co-design is further demonstrated by providing a hardware prototype on an open-source RISC-V based System-on-a-Chip (SoC) platform. The third research direction covered in this dissertation focuses on lattice-based cryptography, which represents one of the most promising and popular alternatives to today\u27s widely adopted public key solutions. Prior research has presented hardware designs targeting the computing blocks that are necessary for the implementation of lattice-based systems. However, a recurrent issue in most existing designs is that these hardware designs are not fully scalable or parameterized, hence limited to specific cryptographic primitives and security parameter sets. The research presented in this dissertation is the first that develops hardware accelerators that are designed to be fully parameterized to support different lattice-based schemes and parameters. Further, these accelerators are utilized to realize the first software-harware co-design of provably-secure instances of qTESLA, which is a lattice-based digital signature scheme. This dissertation demonstrates that even demanding, provably-secure schemes can be realized efficiently with proper use of software-hardware co-design. The final research presented in this dissertation is focused on the isogeny-based scheme SIKE, which recently made it to the final round of the PQC standardization process. This research shows that hardware accelerators can be designed to offload compute-intensive elliptic curve and isogeny computations to hardware in a versatile fashion. These hardware accelerators are designed to be fully parameterized to support different security parameter sets of SIKE as well as flexible hardware configurations targeting different user applications. This research is the first that presents versatile hardware accelerators for SIKE that can be mapped efficiently to both FPGA and ASIC platforms. Based on these accelerators, an efficient software-hardwareco-design is constructed for speeding up SIKE. In the end, this dissertation demonstrates that, despite being embedded with expensive arithmetic, the isogeny-based SIKE scheme can be run efficiently by exploiting specialized hardware. These four research directions combined demonstrate the practicability of building efficient hardware architectures for complex PQC algorithms. The exploration of efficient PQC solutions for different hardware platforms will eventually help migrate high-end servers and low-end embedded devices towards the post-quantum era