Design synthesis for dynamically reconfigurable logic systems

Dynamic reconfiguration of logic circuits has been a research problem for over four decades. While applications using logic reconfiguration in practical scenarios have been demonstrated, the design of these systems has proved to be a difficult process demanding the skills of an experienced reconfigurable logic design expert. This thesis proposes an automatic synthesis method which relieves designers of some of the difficulties associated with designing partially dynamically reconfigurable systems. A new design abstraction model for reconfigurable systems is proposed in order to support design exploration using the presented method. Given an input behavioural model, a technology server and a set of design constraints, the method will generate a reconfigurable design solution in the form of a 3D floorplan and a configuration schedule. The approach makes use of genetic algorithms. It facilitates global optimisation to accommodate multiple design objectives common in reconfigurable system design, while making realistic estimates of configuration overheads and of the potential for resource sharing between configurations. A set of custom evolutionary operators has been developed to cope with a multiple-objective search space. Furthermore, the application of a simulation technique verifying the lll results of such an automatic exploration is outlined in the thesis. The qualities of the proposed method are evaluated using a set of benchmark designs taking data from a real reconfigurable logic technology. Finally, some extensions to the proposed method and possible research directions are discussed

Fonctions élémentaires en virgule flottante pour les accélérateurs reconfigurables

National audienceLes circuits reconfigurables FPGA ont désormais une capacité telle qu'ils peuvent être utilisés à des tâches d'accélération de calcul en virgule flottante. La littérature (et depuis peu les constructeurs) proposent des opérateurs pour les quatre opérations. L'étape suivante est de proposer des opérateurs pour les fonctions élémentaires les plus utilisées. Parmi celles-ci, nous proposons des architectures dédiées pour l'évaluation des fonctions exponentielles, logarithme, sinus et cosinus, et étudions les compromis possibles. Pour chacune de ces fonctions, un seul de ces opérateurs surpasse d'un facteur dix les processeurs généralistes en terme de débit, tout en occupant une fraction des ressources matérielles du FPGA. Tous ces opérateurs sont disponibles librement sur http://www.ens-lyon.fr/LIP/Arenaire/

Rethinking FPGA Architectures for Deep Neural Network applications

The prominence of machine learning-powered solutions instituted an unprecedented trend of integration into virtually all applications with a broad range of deployment constraints from tiny embedded systems to large-scale warehouse computing machines. While recent research confirms the edges of using contemporary FPGAs to deploy or accelerate machine learning applications, especially where the latency and energy consumption are strictly limited, their pre-machine learning optimised architectures remain a barrier to the overall efficiency and performance. Realizing this shortcoming, this thesis demonstrates an architectural study aiming at solutions that enable hidden potentials in the FPGA technology, primarily for machine learning algorithms. Particularly, it shows how slight alterations to the state-of-the-art architectures could significantly enhance the FPGAs toward becoming more machine learning-friendly while maintaining the near-promised performance for the rest of the applications. Eventually, it presents a novel systematic approach to deriving new block architectures guided by designing limitations and machine learning algorithm characteristics through benchmarking. First, through three modifications to Xilinx DSP48E2 blocks, an enhanced digital signal processing (DSP) block for important computations in embedded deep neural network (DNN) accelerators is described. Then, two tiers of modifications to FPGA logic cell architecture are explained that deliver a variety of performance and utilisation benefits with only minor area overheads. Eventually, with the goal of exploring this new design space in a methodical manner, a problem formulation involving computing nested loops over multiply-accumulate (MAC) operations is first proposed. A quantitative methodology for deriving efficient coarse-grained compute block architectures from benchmarks is then suggested together with a family of new embedded blocks, called MLBlocks

Using embedded hardware monitor cores in critical computer systems

The integration of FPGA devices in many different architectures and services makes monitoring and real time detection of errors an important concern in FPGA system design. A monitor is a tool, or a set of tools, that facilitate analytic measurements in observing a given system. The goal of these observations is usually the performance analysis and optimisation, or the surveillance of the system. However, System-on-Chip (SoC) based designs leave few points to attach external tools such as logic analysers. Thus, an embedded error detection core that allows observation of critical system nodes (such as processor cores and buses) should enforce the operation of the FPGA-based system, in order to prevent system failures. The core should not interfere with system performance and must ensure timely detection of errors. This thesis is an investigation onto how a robust hardware-monitoring module can be efficiently integrated in a target PCI board (with FPGA-based application processing features) which is part of a critical computing system. [Continues.

A Field Programmable Gate Array Architecture for Two-Dimensional Partial Reconfiguration

Reconfigurable machines can accelerate many applications by adapting to their needs through hardware reconfiguration. Partial reconfiguration allows the reconfiguration of a portion of a chip while the rest of the chip is busy working on tasks. Operating system models have been proposed for partially reconfigurable machines to handle the scheduling and placement of tasks. They are called OS4RC in this dissertation. The main goal of this research is to address some problems that come from the gap between OS4RC and existing chip architectures and the gap between OS4RC models and practical applications. Some existing OS4RC models are based on an impractical assumption that there is no data exchange channel between IP (Intellectual Property) circuits residing on a Field Programmable Gate Array (FPGA) chip and between an IP circuit and FPGA I/O pins. For models that do not have such an assumption, their inter-IP communication channels have severe drawbacks. Those channels do not work well with 2-D partial reconfiguration. They are not suitable for intensive data stream processing. And frequently they are very complicated to design and very expensive. To address these problems, a new chip architecture that can better support inter-IP and IP-I/O communication is proposed and a corresponding OS4RC kernel is then specified. The proposed FPGA architecture is based on an array of clusters of configurable logic blocks, with each cluster serving as a partial reconfiguration unit, and a mesh of segmented buses that provides inter-IP and IP-I/O communication channels. The proposed OS4RC kernel takes care of the scheduling, placement, and routing of circuits under the constraints of the proposed architecture. Features of the new architecture in turns reduce the kernel execution times and enable the runtime scheduling, placement and routing. The area cost and the configuration memory size of the new chip architecture are calculated and analyzed. And the efficiency of the OS4RC kernel is evaluated via simulation using three different task models

Comparison of logarithmic and floating-point number systems implemented on Xilinx Virtex-II field-programmable gate arrays

The aim of this thesis is to compare the implementation of parameterisable LNS (logarithmic number system) and floating-point high dynamic range number systems on FPGA. The Virtex/Virtex-II range of FPGAs from Xilinx, which are the most popular FPGA technology, are used to implement the designs. The study focuses on using the low level primitives of the technology in an efficient way and so initially the design issues in implementing fixed-point operators are considered. The four basic operations of addition, multiplication, division and square root are considered. Carry- free adders, ripple-carry adders, parallel multipliers and digit recurrence division and square root are discussed. The floating-point operators use the word format and exceptions as described by the IEEE std-754. A dual-path adder implementation is described in detail, as are floating-point multiplier, divider and square root components. Results and comparisons with other works are given. The efficient implementation of function evaluation methods is considered next. An overview of current FPGA methods is given and a new piecewise polynomial implementation using the Taylor series is presented and compared with other designs in the literature. In the next section the LNS word format, accuracy and exceptions are described and two new LNS addition/subtraction function approximations are described. The algorithms for performing multiplication, division and powering in the LNS domain are also described and are compared with other designs in the open literature. Parameterisable conversion algorithms to convert to/from the fixed-point domain from/to the LNS and floating-point domain are described and implementation results given. In the next chapter MATLAB bit-true software models are given that have the exact functionality as the hardware models. The interfaces of the models are given and a serial communication system to perform low speed system tests is described. A comparison of the LNS and floating-point number systems in terms of area and delay is given. Different functions implemented in LNS and floating-point arithmetic are also compared and conclusions are drawn. The results show that when the LNS is implemented with a 6-bit or less characteristic it is superior to floating-point. However, for larger characteristic lengths the floating-point system is more efficient due to the delay and exponential area increase of the LNS addition operator. The LNS is beneficial for larger characteristics than 6-bits only for specialist applications that require a high portion of division, multiplication, square root, powering operations and few additions

Database System Acceleration on FPGAs

Relational database systems provide various services and applications with an efficient means for storing, processing, and retrieving their data. The performance of these systems has a direct impact on the quality of service of the applications that rely on them. Therefore, it is crucial that database systems are able to adapt and grow in tandem with the demands of these applications, ensuring that their performance scales accordingly. In the past, Moore's law and algorithmic advancements have been sufficient to meet these demands. However, with the slowdown of Moore's law, researchers have begun exploring alternative methods, such as application-specific technologies, to satisfy the more challenging performance requirements. One such technology is field-programmable gate arrays (FPGAs), which provide ideal platforms for developing and running custom architectures for accelerating database systems. The goal of this thesis is to develop a domain-specific architecture that can enhance the performance of in-memory database systems when executing analytical queries. Our research is guided by a combination of academic and industrial requirements that seek to strike a balance between generality and performance. The former ensures that our platform can be used to process a diverse range of workloads, while the latter makes it an attractive solution for high-performance use cases. Throughout this thesis, we present the development of a system-on-chip for database system acceleration that meets our requirements. The resulting architecture, called CbMSMK, is capable of processing the projection, sort, aggregation, and equi-join database operators and can also run some complex TPC-H queries. CbMSMK employs a shared sort-merge pipeline for executing all these operators, which results in an efficient use of FPGA resources. This approach enables the instantiation of multiple acceleration cores on the FPGA, allowing it to serve multiple clients simultaneously. CbMSMK can process both arbitrarily deep and wide tables efficiently. The former is achieved through the use of the sort-merge algorithm which utilizes the FPGA RAM for buffering intermediate sort results. The latter is achieved through the use of KeRRaS, a novel variant of the forward radix sort algorithm introduced in this thesis. KeRRaS allows CbMSMK to process a table a few columns at a time, incrementally generating the final result through multiple iterations. Given that acceleration is a key objective of our work, CbMSMK benefits from many performance optimizations. For instance, multi-way merging is employed to reduce the number of merge passes required for the execution of the sort-merge algorithm, thus improving the performance of all our pipeline-breaking operators. Another example is our in-depth analysis of early aggregation, which led to the development of a novel cache-based algorithm that significantly enhances aggregation performance. Our experiments demonstrate that CbMSMK performs on average 5 times faster than the state-of-the-art CPU-based database management system MonetDB.:I Database Systems & FPGAs 1 INTRODUCTION 1.1 Databases & the Importance of Performance 1.2 Accelerators & FPGAs 1.3 Requirements 1.4 Outline & Summary of Contributions 2 BACKGROUND ON DATABASE SYSTEMS 2.1 Databases 2.1.1 Storage Model 2.1.2 Storage Medium 2.2 Database Operators 2.2.1 Projection 2.2.2 Filter 2.2.3 Sort 2.2.4 Aggregation 2.2.5 Join 2.2.6 Operator Classification 2.3 Database Queries 2.4 Impact of Acceleration 3 BACKGROUND ON FPGAS 3.1 FPGA 3.1.1 Logic Element 3.1.2 Block RAM (BRAM) 3.1.3 Digital Signal Processor (DSP) 3.1.4 IO Element 3.1.5 Programmable Interconnect 3.2 FPGADesignFlow 3.2.1 Specifications 3.2.2 RTL Description 3.2.3 Verification 3.2.4 Synthesis, Mapping, Placement, and Routing 3.2.5 TimingAnalysis 3.2.6 Bitstream Generation and FPGA Programming 3.3 Implementation Quality Metrics 3.4 FPGA Cards 3.5 Benefits of Using FPGAs 3.6 Challenges of Using FPGAs 4 RELATED WORK 4.1 Summary of Related Work 4.2 Platform Type 4.2.1 Accelerator Card 4.2.2 Coprocessor 4.2.3 Smart Storage 4.2.4 Network Processor 4.3 Implementation 4.3.1 Loop-based implementation 4.3.2 Sort-based Implementation 4.3.3 Hash-based Implementation 4.3.4 Mixed Implementation 4.4 A Note on Quantitative Performance Comparisons II Cache-Based Morphing Sort-Merge with KeRRaS (CbMSMK) 5 OBJECTIVES AND ARCHITECTURE OVERVIEW 5.1 From Requirements to Objectives 5.2 Architecture Overview 5.3 Outlineof Part II 6 COMPARATIVE ANALYSIS OF OPENCL AND RTL FOR SORT-MERGE PRIMITIVES ON FPGAS 6.1 Programming FPGAs 6.2 RelatedWork 6.3 Architecture 6.3.1 Global Architecture 6.3.2 Sorter Architecture 6.3.3 Merger Architecture 6.3.4 Scalability and Resource Adaptability 6.4 Experiments 6.4.1 OpenCL Sort-Merge Implementation 6.4.2 RTLSorters 6.4.3 RTLMergers 6.4.4 Hybrid OpenCL-RTL Sort-Merge Implementation 6.5 Summary & Discussion 7 RESOURCE-EFFICIENT ACCELERATION OF PIPELINE-BREAKING DATABASE OPERATORS ON FPGAS 7.1 The Case for Resource Efficiency 7.2 Related Work 7.3 Architecture 7.3.1 Sorters 7.3.2 Sort-Network 7.3.3 X:Y Mergers 7.3.4 Merge-Network 7.3.5 Join Materialiser (JoinMat) 7.4 Experiments 7.4.1 Experimental Setup 7.4.2 Implementation Description & Tuning 7.4.3 Sort Benchmarks 7.4.4 Aggregation Benchmarks 7.4.5 Join Benchmarks 7. Summary 8 KERRAS: COLUMN-ORIENTED WIDE TABLE PROCESSING ON FPGAS 8.1 The Scope of Database System Accelerators 8.2 Related Work 8.3 Key-Reduce Radix Sort(KeRRaS) 8.3.1 Time Complexity 8.3.2 Space Complexity (Memory Utilization) 8.3.3 Discussion and Optimizations 8.4 Architecture 8.4.1 MSM 8.4.2 MSMK: Extending MSM with KeRRaS 8.4.3 Payload, Aggregation and Join Processing 8.4.4 Limitations 8.5 Experiments 8.5.1 Experimental Setup 8.5.2 Datasets 8.5.3 MSMK vs. MSM 8.5.4 Payload-Less Benchmarks 8.5.5 Payload-Based Benchmarks 8.5.6 Flexibility 8.6 Summary 9 A STUDY OF EARLY AGGREGATION IN DATABASE QUERY PROCESSING ON FPGAS 9.1 Early Aggregation 9.2 Background & Related Work 9.2.1 Sort-Based Early Aggregation 9.2.2 Cache-Based Early Aggregation 9.3 Simulations 9.3.1 Datasets 9.3.2 Metrics 9.3.3 Sort-Based Versus Cache-Based Early Aggregation 9.3.4 Comparison of Set-Associative Caches 9.3.5 Comparison of Cache Structures 9.3.6 Comparison of Replacement Policies 9.3.7 Cache Selection Methodology 9.4 Cache System Architecture 9.4.1 Window Aggregator 9.4.2 Compressor & Hasher 9.4.3 Collision Detector 9.4.4 Collision Resolver 9.4.5 Cache 9.5 Experiments 9.5.1 Experimental Setup 9.5.2 Resource Utilization and Parameter Tuning 9.5.3 Datasets 9.5.4 Benchmarks on Synthetic Data 9.5.5 Benchmarks on Real Data 9.6 Summary 10 THE FULL PICTURE 10.1 System Architecture 10.2 Benchmarks 10.3 Meeting the Objectives III Conclusion 11 SUMMARY AND OUTLOOK ON FUTURE RESEARCH 11.1 Summary 11.2 Future Work BIBLIOGRAPHY LIST OF FIGURES LIST OF TABLE

Unifying software and hardware of multithreaded reconfigurable applications within operating system processes

Novel reconfigurable System-on-Chip (SoC) devices offer combining software with application-specific hardware accelerators to speed up applications. However, by mixing user software and user hardware, principal programming abstractions and system-software commodities are usually lost, since hardware accelerators (1) do not have execution context —it is typically the programmer who is supposed to provide it, for each accelerator, (2) do not have virtual memory abstraction —it is again programmer who shall communicate data from user software space to user hardware, even if it is usually burdensome (or sometimes impossible!), (3) cannot invoke system services (e.g., to allocate memory, open files, communicate), and (4) are not easily portable —they depend mostly on system-level interfacing, although they logically belong to the application level. We introduce a unified Operating System (OS) process for codesigned reconfigurable applications that provides (1) unified memory abstraction for software and hardware application parts, (2) execution transfers from software to hardware and vice versa, thus enabling hardware accelerators to use systems services and callback other software and hardware functions, and (3) multithreaded execution of multiple software and hardware threads. The unified OS process ensures portability of codesigned applications, by providing standardised means of interfacing. Having just-another abstraction layer usually affects performance: we show that the runtime optimisations in the system layer supporting the unified OS process can minimise the performance loss and even outperform typical approaches. The unified OS process also fosters unrestricted automated synthesis of software to hardware, thus allowing unlimited migration of application components. We demonstrate the advantages of the unified OS process in practice, for Linux systems running on Xilinx Virtex-II Pro and Altera Excalibur reconfigurable devices