VThreads: A novel VLIW chip multiprocessor with hardware-assisted PThreads

We discuss VThreads, a novel VLIW CMP with hardware-assisted shared-memory Thread support. VThreads supports Instruction Level Parallelism via static multiple-issue and Thread Level Parallelism via hardware-assisted POSIX Threads along with extensive customization. It allows the instantiation of tightlycoupled streaming accelerators and supports up to 7-address Multiple-Input, Multiple-Output instruction extensions. VThreads is designed in technology-independent Register-Transfer-Level VHDL and prototyped on 40 nm and 28 nm Field-Programmable gate arrays. It was evaluated against a PThreads-based multiprocessor based on the Sparc-V8 ISA. On a 65 nm ASIC implementation VThreads achieves up to x7.2 performance increase on synthetic benchmarks, x5 on a parallel Mandelbrot implementation, 66% better on a threaded JPEG implementation, 79% better on an edge-detection benchmark and ~13% improvement on DES compared to the Leon3MP CMP. In the range of 2 to 8 cores VThreads demonstrates a post-route (statistical) power reduction between 65% to 57% at an area increase of 1.2%-10% for 1-8 cores, compared to a similarly-configured Leon3MP CMP. This combination of micro-architectural features, scalability, extensibility, hardware support for low-latency PThreads, power efficiency and area make the processor an attractive proposition for low-power, deeply-embedded applications requiring minimum OS support

Code Generation for an Application-Specific VLIW Processor With Clustered, Addressable Register Files

International audienceModern compilers integrate recent advances in compiler construction, intermediate representations, algorithms and programming language front-ends. Yet code generation for appli\-cation-specific architectures benefits only marginally from this trend, as most of the effort is oriented towards popular general-purpose architectures. Historically, non-orthogonal architectures have relied on custom compiler technologies, some retargettable, but largely decoupled from the evolution of mainstream tool flows. Very Long Instruction Word (VLIW) architectures have introduced a variety of interesting problems such as clusterization, packetization or bundling, instruction scheduling for exposed pipelines, long delay slots, software pipelining, etc. These have been addressed in the literature, with a focus on the exploitation of Instruction Level Parallelism (ILP). While these are well known solutions already embedded into existing compilers, they rely on common hardware functionalities that are expected to be present in a fairly large subset of VLIW architectures. This paper presents our work on back-end compiler for Mephisto, a high performance low-power application-specific processor, based on LLVM. Mephisto is specialized enough to challenge established code generation solutions for VLIW and DSP processors, calling for an innovative compilation flow. Conversely, even though Mephisto might be seen a somewhat exotic processor, its hardware characteristics such as addressable register files benefit from existing analyses and transformations in LLVM. We describe our model of the Mephisto architecture, the difficulties we encountered, and the associated compilation methods, some of them new and specific to Mephisto

An automated OpenCL FPGA compilation framework targeting a configurable, VLIW chip multiprocessor

Modern system-on-chips augment their baseline CPU with coprocessors and accelerators to increase overall computational capacity and power efficiency, and thus have evolved into heterogeneous systems. Several languages have been developed to enable this paradigm shift, including CUDA and OpenCL. This thesis discusses a unified compilation environment to enable heterogeneous system design through the use of OpenCL and a customised VLIW chip multiprocessor (CMP) architecture, known as the LE1. An LLVM compilation framework was researched and a prototype developed to enable the execution of OpenCL applications on the LE1 CPU. The framework fully automates the compilation flow and supports work-item coalescing to better utilise the CPU cores and alleviate the effects of thread divergence. This thesis discusses in detail both the software stack and target hardware architecture and evaluates the scalability of the proposed framework on a highly precise cycle-accurate simulator. This is achieved through the execution of 12 benchmarks across 240 different machine configurations, as well as further results utilising an incomplete development branch of the compiler. It is shown that the problems generally scale well with the LE1 architecture, up to eight cores, when the memory system becomes a serious bottleneck. Results demonstrate superlinear performance on certain benchmarks (x9 for the bitonic sort benchmark with 8 dual-issue cores) with further improvements from compiler optimisations (x14 for bitonic with the same configuration

The Potential for a GPU-Like Overlay Architecture for FPGAs

We propose a soft processor programming model and architecture inspired by graphics processing units (GPUs) that are well-matched to the strengths of FPGAs, namely, highly parallel and pipelinable computation. In particular, our soft processor architecture exploits multithreading, vector operations, and predication to supply a floating-point pipeline of 64 stages via hardware support for up to 256 concurrent thread contexts. The key new contributions of our architecture are mechanisms for managing threads and register files that maximize data-level and instruction-level parallelism while overcoming the challenges of port limitations of FPGA block memories as well as memory and pipeline latency. Through simulation of a system that (i) is programmable via NVIDIA's high-level Cg language, (ii) supports AMD's CTM r5xx GPU ISA, and (iii) is realizable on an XtremeData XD1000 FPGA-based accelerator system, we demonstrate the potential for such a system to achieve 100% utilization of a deeply pipelined floating-point datapath

Doctor of Philosophy

dissertationThe embedded system space is characterized by a rapid evolution in the complexity and functionality of applications. In addition, the short time-to-market nature of the business motivates the use of programmable devices capable of meeting the conflicting constraints of low-energy, high-performance, and short design times. The keys to achieving these conflicting constraints are specialization and maximally extracting available application parallelism. General purpose processors are flexible but are either too power hungry or lack the necessary performance. Application-specific integrated circuits (ASICS) efficiently meet the performance and power needs but are inflexible. Programmable domain-specific architectures (DSAs) are an attractive middle ground, but their design requires significant time, resources, and expertise in a variety of specialties, which range from application algorithms to architecture and ultimately, circuit design. This dissertation presents CoGenE, a design framework that automates the design of energy-performance-optimal DSAs for embedded systems. For a given application domain and a user-chosen initial architectural specification, CoGenE consists of a a Compiler to generate execution binary, a simulator Generator to collect performance/energy statistics, and an Explorer that modifies the current architecture to improve energy-performance-area characteristics. The above process repeats automatically until the user-specified constraints are achieved. This removes or alleviates the time needed to understand the application, manually design the DSA, and generate object code for the DSA. Thus, CoGenE is a new design methodology that represents a significant improvement in performance, energy dissipation, design time, and resources. This dissertation employs the face recognition domain to showcase a flexible architectural design methodology that creates "ASIC-like" DSAs. The DSAs are instruction set architecture (ISA)-independent and achieve good energy-performance characteristics by coscheduling the often conflicting constraints of data access, data movement, and computation through a flexible interconnect. This represents a significant increase in programming complexity and code generation time. To address this problem, the CoGenE compiler employs integer linear programming (ILP)-based 'interconnect-aware' scheduling techniques for automatic code generation. The CoGenE explorer employs an iterative technique to search the complete design space and select a set of energy-performance-optimal candidates. When compared to manual designs, results demonstrate that CoGenE produces superior designs for three application domains: face recognition, speech recognition and wireless telephony. While CoGenE is well suited to applications that exhibit a streaming behavior, multithreaded applications like ray tracing present a different but important challenge. To demonstrate its generality, CoGenE is evaluated in designing a novel multicore N-wide SIMD architecture, known as StreamRay, for the ray tracing domain. CoGenE is used to synthesize the SIMD execution cores, the compiler that generates the application binary, and the interconnection subsystem. Further, separating address and data computations in space reduces data movement and contention for resources, thereby significantly improving performance compared to existing ray tracing approaches

Evaluating Cache Coherent Shared Virtual Memory for Heterogeneous Multicore Chips

The trend in industry is towards heterogeneous multicore processors (HMCs), including chips with CPUs and massively-threaded throughput-oriented processors (MTTOPs) such as GPUs. Although current homogeneous chips tightly couple the cores with cache-coherent shared virtual memory (CCSVM), this is not the communication paradigm used by any current HMC. In this paper, we present a CCSVM design for a CPU/MTTOP chip, as well as an extension of the pthreads programming model, called xthreads, for programming this HMC. Our goal is to evaluate the potential performance benefits of tightly coupling heterogeneous cores with CCSVM

On the automated compilation of UML notation to a VLIW chip multiprocessor

With the availability of more and more cores within architectures the process of extracting implicit and explicit parallelism in applications to fully utilise these cores is becoming complex. Implicit parallelism extraction is performed through the inclusion of intelligent software and hardware sections of tool chains although these reach their theoretical limit rather quickly. Due to this the concept of a method of allowing explicit parallelism to be performed as fast a possible has been investigated. This method enables application developers to perform creation and synchronisation of parallel sections of an application at a finer-grained level than previously possible, resulting in smaller sections of code being executed in parallel while still reducing overall execution time. Alongside explicit parallelism, a concept of high level design of applications destined for multicore systems was also investigated. As systems are getting larger it is becoming more difficult to design and track the full life-cycle of development. One method used to ease this process is to use a graphical design process to visualise the high level designs of such systems. One drawback in graphical design is the explicit nature in which systems are required to be generated, this was investigated, and using concepts already in use in text based programming languages, the generation of platform-independent models which are able to be specialised to multiple hardware architectures was developed. The explicit parallelism was performed using hardware elements to perform thread management, this resulted in speed ups of over 13 times when compared to threading libraries executed in software on commercially available processors. This allowed applications with large data dependent sections to be parallelised in small sections within the code resulting in a decrease of overall execution time. The modelling concepts resulted in the saving of between 40-50% of the time and effort required to generate platform-specific models while only incurring an overhead of up to 15% the execution cycles of these models designed for specific architectures

Improving multithreading performance for clustered VLIW architectures.

Very Long Instruction Word (VLIW) processors are very popular in embedded and mobile computing domain. Use of VLIW processors range from Digital Signal Processors (DSPs) found in a plethora of communication and multimedia devices to Graphics Processing Units (GPUs) used in gaming and high performance computing devices. The advantage of VLIWs is their low complexity and low power design which enable high performance at a low cost. Scalability of VLIWs is limited by the scalability of register file ports. It is not viable to have a VLIW processor with a single large register file because of area and power consumption implications of the register file. Clustered VLIW solve the register file scalability issue by partitioning the register file into multiple clusters and a set of functional units that are attached to register file of that cluster. Using a clustered approach, higher issue width can be achieved while keeping the cost of register file within reasonable limits. Several commercial VLIW processors have been designed using the clustered VLIW model. VLIW processors can be used to run a larger set of applications. Many of these applications have a good Lnstruction Level Parallelism (ILP) which can be efficiently utilized. However, several applications, specially the ones that are control code dominated do not exibit good ILP and the processor is underutilized. Cache misses is another major source of resource underutiliztion. Multithreading is a popular technique to improve processor utilization. Interleaved MultiThreading (IMT) hides cache miss latencies by scheduling a different thread each cycle but cannot hide unused instructions slots. Simultaneous MultiThread (SMT) can also remove ILP under-utilization by issuing multiple threads to fill the empty instruction slots. However, SMT has a higher implementation cost than IMT. The thesis presents Cluster-level Simultaneous MultiThreading (CSMT) that supports a limited form of SMT where VLIW instructions from different threads are merged at a cluster-level granularity. This lowers the hardware implementation cost to a level comparable to the cheap IMT technique. The more complex SMT combines VLIW instructions at the individual operation-level granularity which is quite expensive especially in for a mobile solution. We refer to SMT at operation-level as OpSMT to reduce ambiguity. While previous studies restricted OpSMT on a VLIW to 2 threads, CSMT has a better scalability and upto 8 threads can be supported at a reasonable cost. The thesis proposes several other techniques to further improve CSMT performance. In particular, Cluster renaming remaps the clusters used by instructions of different threads to reduce resource conflicts. Cluster renaming is quite effective in reducing the issue-slots under-utilization and significantly improves CSMT performance.The thesis also proposes: a hybrid between IMT and CSMT which increases the number of supported threads, heterogeneous instruction merging where some instructions are combined using SMT and CSMT rest, and finally, split-issue, a technique that allows to launch partially an instruction making it easier to be combined with others