Performance analysis of inter cluster communication methods in VLIW architecture

With increasing demands for performance by embedded systems, especially by digital signal processing (DSP) applications, embedded processors must increase available instructionlevel parallelism (ILP) within significant constraints on power consumption and chip cost. Unfortunately, supporting a large amount of ILP on a processor while maintaining a single register file increases chip cost and potentially decreases overall performance due to increased cycle time. To address this problem, some modern embedded processors partition the register file into multiple low-ported register files, each directly connected with one or more functional units. These functional unit/register file groups are called clusters. Clustered VLIW (very long instruction word) architectures need extra copy operations or delays to transfer values among clusters. To take advantage of clustered architectures, the compiler must expose parallelism for maximal functional-unit utilization, and schedule instructions to reduce intercluster communication overhead. High-level loop transformations offer an excellent opportunity to enhance the abilities of low-level optimizers to generate code for clustered architectures. This dissertation investigates the effects of three loop transformations, i.e., loop fusion, loop unrolling, and unroll-and-jam, on clustered VLIW architectures. The objective is to achieve high performance with low communication overhead. This dissertation discusses the following techniques: Loop Fusion This research examines the impact of loop fusion on clustered architectures. A metric based upon communication costs for guiding loop fusion is developed and tested on DSP benchmarks. Unroll-and-jam and Loop Unrolling A new method that integrates a communication cost model with an integer-optimization problem is developed to determine unroll amounts for loop unrolling and unroll-and-jam automatically for a specific loop on a specific architecture. These techniques have been implemented and tested using DSP benchmarks on simulated, clustered VLIW architectures and a real clustered, embedded processor, the TI TMS320C64X. The results show that the new techniques achieve an average speedup of 1.72-1.89 on five different clustered architectures. These techniques have been implemented and tested using DSP benchmarks on simulated, clustered VLIW architectures and a real clustered, embedded processor, the TI TMS320C64X. The results show that the new techniques achieve an average speedup of 1.72-1.89 on five different clustered architectures.

Very Long Instruction Word (VLIW) architectures enhance performance by exploiting fin-egrained instruction level parallelism. In this paper, we describe the development of two compiler assisted multiple instruction word retry schemes for VLIW architectures. The first scheme utilizes the compiler techniques previously developed for processors with single functional units Compiler generated hazard-free code with different degrees of rollback capability for uni-processors is compacted by a modified VLIW trace scheduling algorithm. Nops are then inserted in the scheduled code words to resolve data hazards for VLIW architectures. Performance is compared under three parameters : N, the rollback distance for uni-processors; P, the number of functional units; and n, the rollback distance for VLIW architectures. The second scheme employs a hardware read buffer [2] to resolve frequently occurring data hazards, and utilizes the compiler to resolve the remaining hazards. Performance results are shown for six benchmark programs.

Efficient matrix inversion based on VLIW architecture

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.

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.

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.

In current Instruction set architecture(ISA) design, fixed length instructions are benefit for improving the efficiency of instruction dispatching. But in embeded computers where memory is limited, variable lengths instructions are much better in memory cost. In this VLIW (Very Long Instruction Word) architecture, a two-staged pipeline is used to expand and dispatch the variable lengths instructions. When CPU receives a packet of instructions, a fixed number of instructions expand in the first pipeline phase. In the second pipeline phase, CPU dispatch instructions which execute in the same pipeline cycle.

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.

Instruction Level Parallelism (ILP) machines, such as Very Long Instruction Word (VLIW) architectures, and customised architectures are two para-digms that are used to increase the performance of processors. While a VLIW machine has multiple functional units, a customised processor is equipped with Application-specific Functional Units (AFUs). Customisation has been proved beneficial on single issue machines, but its effect on multiple issue machines remains unanswered. Is a VLIW machine powerful enough to nullify the benefit of customisation? Or are the two benefits orthogonal and can be exploited together? In this paper, we answer positively to the latter question. We experimentally prove that insertion of automatically identified AFUs can improve performance of a VLIW architecture, and allow the designer of ILP processor to trade-off either issue-width or register file size. We have customised the Trimaran architecture and toolchain framework to model AFUs accurately and discuss the challenges of adding instruction-set extension support to a legacy toolchain.

Java bytecodes can be executed with the following three methods: a Java interpreter running on a particular machine interprets bytecodes; a Just-in-Time (JIT) compiler translates bytecodes to the native primitives of the particular machine and the machine executes the translated codes; and a Java processor executes bytecodes directly. The first two methods require no special hardware support for the execution of Java bytecodes and are widely used currently. The last method requires an embedded Java processor, picoJavaI or picoJavaII for instance. The picoJavaI and picoJavaII are simple pipelined processors with no ILP (instruction level parallelism) and TLP (thread level parallelism) supports. A so-called MAJC (microprocessor architecture for Java computing) design can exploit ILP and TLP by using a modified VLIW (very long instruction word) architecture and vertical multithreading technique, but it has its own instruction set and cannot execute Java bytecodes directly. In this paper, we investigate a processor architecture which can directly execute Java bytecodes meanwhile can exploit Java ILP and TLP simultaneously. The proposed processor consists of multiple slots implementing horizontal multithreading and multiple functional units shared by all threads executed in parallel. Our architectural simulation results show that the Java processor could achieve an average 20 IPC (instructions per cycle), or 7.33 EIPC (effective IPC), with 8 slots and a 4-instruction scheduling window for each slot. We also check other configurations and give the utilization of functional units as well as the performance improvement with various kinds of working loads.

SUMMARYDigital signal processors (DSPs) with very long instruction word (VLIW) data‐path architectures are increasingly being deployed on embedded devices for multimedia processing applications. To reduce the power consumption and design cost of VLIW DSP processors, distributed register files and multibank register architectures are being adopted to reduce the number of read and write ports associated with register files, which presents new challenges for devising compiler optimization schemes. This paper addresses the issues of reducing the spill code for a VLIW DSP with distributed register files. Spill code produced by register allocation is traditionally handled by memory spills, but the multibank register‐file architecture provides the opportunity to spill‐out register values onto different register banks. We present a conceptual framework based on the universal and the proxy interference graphs to model the live ranges of registers for spilling codes to different register banks. Heuristic algorithms are then developed on the basis of this concept. By heuristically estimating the register pressure for each register file, we treat different register banks as optional spilling locations in addition to traditional spilling to memory. Experiments were performed on the parallel architecture core VLIW DSP with distributed register files by incorporating our proposed optimization schemes into an Open64‐based compiler. The experimental results show that our approach can improve the performances on average for DSPStone and MiBench benchmarks with spilling cases by 7.1% and 21.6%, respectively, compared with the one always handling spill code in memory. Copyright © 2013 John Wiley & Sons, Ltd.

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.

Nearly all personal computer and workstation processors, and virtually all high-performance embedded processor cores, now embody instruction level parallel (ILP) processing in the form of superscalar or very long instruction word (VLIW) architectures. ILP processors put much more of a burden on compilers; without heroic compiling techniques, most such processors fall far short of their performance goals. Those techniques are largely found in the high-level optimization phase and in the code generation phase; they are also collectively called instruction scheduling. This paper reviews the state of the art in code generation for ILP parallel processors. Modern ILP code generation methods move code across basic block boundaries. These methods grew out of techniques for generating horizontal microcode, so we introduce the problem by describing its history. Most modem approaches can be categorized by the shape of the scheduling region. Some of these regions are loops, and for those techniques known broadly as are used. Software Pipelining techniques are only considered here when there are issues relevant to the region-based techniques presented. The selection of a type of region to use in this process is one of the most controversial questions in code generation; the paper surveys the best known alternatives. The paper then considers two questions: First, given a type of region, how does one pick specific regions of that type in the intermediate code. In conjunction with region selection, we consider region enlargement techniques such as unrolling and branch target expansion. The second question, how does one construct a schedule once regions have been selected, occupies the next section of the paper. Finally, schedule construction using recent, innovative resource modeling based on finite-state automata is then reexamined. The paper includes an extensive bibliography.

A new proposal of a very long instruction word (VLIW) architecture for application specific processors with the built-in-self-repair (BISR) facility realized by means of the variable accuracy arithmetic has been described in this paper. The proposed idea, which is particularly interesting for the portable embedded systems, is based on a novel two accumulator model, which is used in order to obtain high accuracy of the result of a series of floating-point additions. The goal of the proposed approach consists in ensuring the functionality of the system even in case of permanent faults of particular building blocks, e.g., of one of the floating point adders. Instead of decreasing the performance of the system or providing redundant hardware, as it is typically done in other approaches, in our present concept merely the accuracy of the floating point accumulation is reduced. Therefore, although the quality of service is reduced, the performance and the overall functionality of the system may remain unchanged. By this means we can also control the power consumption, saving the power with the cost of the somehow reduced signal processing accuracy.

A limiting performance factor for soft cores that exploit high instruction-level parallelism (ILP) is the need of a high performance multiport memory to provide data at the rate it can be consumed by the available functional units. At the same time, FPGAs contain block RAMs (BRAMs) that provide enormous bandwidth, especially when data is spread through multiple blocks of independent address spaces. We present a novel technique to cope with the multiport memory problem and increase performance in very long instruction word (VLIW) FPGA-based soft-core processors. We emulate the use of a multi-ported memory system through the use of multiple single-ported memories, which are controlled at the software level. Experimental results demonstrate that our technique can improve performance on data-driven and control-driven applications where data reuse is found. Measurements show performance improvements of up to 2.15x for a Filter benchmark, a data-driven application, and 1.25x for a Knuth-Morris-Pratt (KMP) string search, a control-driven application. These improvements are achieved while maintaining the same area of the baseline soft processor core.