Architectural time-predictability factor (ATF)

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.

In recent years, very long instruction word (VLIW) processor has attracted much attention in that it offers a high instruction level parallelism and reduces the hardware design complexity. In this paper, we present two fault-tolerant schemes for VLIW processors. The first one is termed as test-instruction scheme which is based on the concept of instruction duplication to detect the errors. The process of test-instruction scheme consists of the error detection, error rollback recovery and reconfiguration. The second approach is called self-checking scheme which adopts the concept of self-checking logic to detect the errors. A real-time error recovery procedure is developed to conquer the errors. We implement the proposed designs of fault-tolerant VLIW processor in VHDL and employ the fault injection and fault simulation to validate our schemes. The main contribution of this research is to present the complete frameworks from error detection to error recovery for fault-tolerant design of VLIW processors. Experience learned from this investigation is that the issues of error detection and error recovery entail considering together. Without taking both issues into account simultaneously, the outcomes may lead to the improper conclusions.

Software-Based Self-Test (SBST) approaches have shown to be an effective solution to detect permanent faults, both at the end of the production process, and during the operational phase. However, when Very Long Instruction Word (VLIW) processors are addressed these techniques require some optimization steps in order to properly exploit the parallelism intrinsic in these architectures. In this paper we present a new method that, starting from previously known algorithms, automatically generates an effective test program able to still reach high fault coverage on the VLIW processor under test, while reducing the test duration and the test code size. The method consists of three parametric phases and can deal with different VLIW processor models. The main goal of the proposed method is to automatically obtain a test program able to effectively reduce the test time and the required resources. Experimental results gathered on a case study show the effectiveness of the proposed approach.

We present MINOTAuR, a timing predictable open source RISC-V core based on the Ariane core [28]. We first modify Ariane in order to make it timing predictable following the approach used to design the SIC processor [12]. We prove that the instruction parallelism in the Ariane core does not prevent from enforcing timing predictability. We further relax restrictions by enabling a limited amount of speculative execution and we are still able to formally prove that the core is timing predictable. Experimental results show that the performance is reduced by only 10% on average compared to the original Ariane core.

Power-balanced instruction scheduling for Very Long Instruction Word (VLIW) processors is an optimization problem which requires a good instruction-level power model for the target processor. Conventionally, these power models are deterministic. However, in reality, there will always be some degree of imprecision involved. For power critical applications, it is desirable to find an optimal schedule which makes sure that the effects of these uncertainties could be minimized. The scheduling algorithm has to be computationally efficient in order to be practical for use in compilers. In this paper, we propose a rule based genetic algorithm to efficiently solve the optimization problem of power-balanced VLIW instruction scheduling with uncertainties in the power consumption model. We theoretically prove our rule-based genetic algorithm can produce as good optimal schedules as the existing algorithms proposed for this problem. Furthermore, its computational efficiency is significantly improved.

The application fields of bytecode virtual machines and Very Long Instruction Word (VLIW) processors overlap in the area of embedded and mobile systems, where the two technologies offer different benefits, namely high code portability, low power consumption and reduced hardware cost. Dynamic compilation makes it possible to bridge the gap between the two technologies, but special attention must be paid to instruction scheduling, which is required in VLIW architectures. While the rewards for dynamic optimization may be high, the trade-offs between optimization benefits and overheads must be fully understood.To this end, we have extended the work of the original JIST project [1], a Virtual Machine and JIT compiler for Java Bytecode targeted to a VLIW processor, to include a full implementation of a superblock scheduler. We show the impact of global scheduling on the performance of code compiled with JIST through the experimental study of a set of benchmark programs. We report significant speedups with respect to the local scheduling version of the JIST compiler.

The performance of Very Long Instruction Word (VLIW) microprocessors depends on the close cooperation between the compiler and the architecture. This paper evaluates a set of important compilation techniques and related architectural features for VLIW machines. The evaluation is performed on a SPARC-based VLIW testbed where gcc-generated optimized SPARC code is scheduled into high-performance VLIW code. As a base scheduling compiler, we experiment with three core scheduling techniques including enhanced pipeline scheduling, all-path speculation, and renaming. We analyze the characteristics of the useful and useless ALUs in each cycle to see how many of those ALUs execute non-speculative operations, speculative operations, and copies, respectively. Then, we evaluate the following compilation techniques: software pipelining, loop unrolling, non-greedy enhanced pipeline scheduling, profile-based all-path speculation, trace-based speculation, renaming, restricted speculative loads, and memory disambiguation. Since we experiment on a uniform testbed based on a detailed analysis of ALUs, our evaluation provides an useful insight on the performance impact of these techniques.

The emerging applications have imposed strong requirements, such as high processing capacity, low‐power consumption, reduced size and many others, on the sensor‐based systems. Owing to their balanced combination of flexibility and hardware performance, digital signal processors (DSPs) have become more and more popular used in sensor‐based systems. Many DSPs have adopted very long instruction words (VLIW) style architecture, for its ability to greatly enhance instruction level parallelism. However, as VLIW codes are statically scheduled, the behaviour of VLIW architecture is dominated by the efficiency of its compiler. Single instruction multiple data (SIMD) instructions, which perform multiple operations in parallel on multiple data packed in registers, have been widely used in DSPs to meet the requirements of sensor‐based systems. Although hand programming still yields the best performing SIMD codes, it is both time consuming and error prone. Advanced compiler techniques to automatically generate SIMD instructions, are under urgent demand. In this study, the authors proposed an SIMD code auto generation approach for VLIW architecture. It recognises candidates of operations in the intermediate representation, evaluates the possibility of grouping them into SIMD code, reconstructs the verified ones according to the cost model and finally generates the SIMD code. The authors have implemented this approach in the compiler of a VLIW DSP named Magnolia, which is designed for sensor‐based systems. The results show that the authors’ approach is very efficient, and can largely enhance the performance.

The run-time performance of VLIW (very long instruction word) microprocessors depends heavily on the effectiveness of its associated optimizing compiler. Typical VLIW compiler phases include instruction scheduling, which maximizes instruction level parallelism (ILP), and register allocation, which minimizes data spills to external memory. If ILP is maximized without considering register constraints, high register pressure may result, leading to increased spill code and reduced run-time performance. In this paper, a new register pressure reduction technique for embedded VLIW processors is presented to control register pressure prior to instruction scheduling and register allocation. By modifying the relative ordering of operations, this technique restructures code to better reduce spills. Our technique has been implemented in Trimaran, an academic VLIW compiler, and evaluated using a series of VLIW benchmarks. Experimental results show that, on average, our algorithm reduces dynamic spills and improves overall cycle counts by 6% for a VLIW architecture with 8 functional units and 32 registers versus previous spill code reduction techniques.

Efficient matrix inversion based on VLIW architecture

Increasing mask costs and decreasing feature sizes together with productivity demand have led to the trend of platform design. Software programmable embedded cores are used to provide the necessary flexibility in integrated systems. Facing increasing system complexity, single-issue digital signal processors (DSPs) have been replaced by cores providing the execution of several instructions in parallel. The most common programming model for multi-issue DSP core architectures is Very Long Instruction Word (VLIW) which is based on static scheduling, and enables minimization of the worst case execution time and reduces core complexity. The drawback of traditional VLIW is poor code density, which leads to high program memory requirements and, therefore, requires a large silicon area of the DSP subsystem. To overcome this problem without limiting the core performance, a scalable long instruction word (xLIW) is introduced. A special align unit is used for implementing the xLIW program memory interface. In this paper, the align unit and its main architectural feature, a scalable instruction buffer, is introduced in detail. xLIW is part of a project for a parameterized DSP core.

With increasing demands for high performance by embedded systems, especially by digital signal processing applications, embedded processors must increase available instruction level parallelism (ILP) within significant constraints on power consumption and chip cost. Clustered VLIW (Very Long Instruction Word) architectures can be used to address this problem. Their clusters have to communicate by some mechanism to ensure that the data in one cluster can be used by other clusters as and when required. We selected four different mechanisms of inter cluster communication under the category of fully connected deadlock free networks. Then we designed and implemented the VLIW processors employing these mechanisms and analyzed them against various performance parameters-cycle time, cycle count overhead, instruction size and gate count. Also the effects of changing the data width and number of registers in a register file are analyzed.

To process enormous 3D data, we have designed a VLIW (Very Long Instruction Word) processor called FLOVA (Floating-Point VLIW Architecture) exploiting the ILP (Instruction-Level Parallelism) in 3D programs. This paper presents FGA (FLOVA Geometry Accelerator) that is the 3D graphics system and it almost removes the time required to process in the geometry stage. We have developed the 3D graphics library, FGA-GL, to supports the FGA system. The deferred primitive rendering algorithm of FGA-GL enables the geometry processing of the primitive data to be done concurrently with the host job such as primitive data management or game play. FGA improves the average performance of 3D graphics system by 2.5-3.0.

The increasing use of digital signal processors (DSPs) in wireless communications and signal processing necessitates the optimization of compilers to support special hardware features. In this paper, we propose a compiler transformation method for zero overhead loop (ZOL). It supports very long instruction word (VLIW), internal branches and the loops whose iterative times are known at runtime and before execution. In addition, for fully exploiting the special architecture features common in DSPs, the compilation of ZOL transformation is optimized, which further reduces the execution time of loop-intensive applications. The method is implemented on Swift which is a DSP architecture with ZOL and VLIW. Experimental results on benchmark programs show that the proposed method is effective in improving performance.

The performance of Very Long Instruction Word (VLIW) microprocessors depends on the close cooperation between the compiler and the architecture. This paper evaluates a set of important compilation techniques and related architectural features for VLIW machines. The evaluation is performed on a SPARC-based VLIW testbed where gcc-generated optimized SPARC code is scheduled into high-performance VLIW code. As a base scheduling compiler, we experiment with three core scheduling techniques including enhanced pipeline scheduling, all-path speculation, and renaming. We analyze the characteristics of the useful and useless ALUs in each cycle to see how many of those ALUs execute non-speculative operations, speculative operations, and copies, respectively. Then, we evaluate the following compilation techniques: software pipelining, loop unrolling, non-greedy enhanced pipeline scheduling, profile-based all-path speculation, trace-based speculation, renaming, restricted speculative loads, and memory disambiguation. Since we experiment on a uniform testbed based on a detailed analysis of ALUs, our evaluation provides an useful insight on the performance impact of these techniques.