IPC Control for Multiple Real-Time Threads on an In-Order SMT Processor

Today’s operating systems were not designed to support the end-to-end real-time requirements of distributed continuous media. Furthermore, the integration of continuous media communications software into such systems poses significant challenges. This paper describes a design for distributed multimedia support in the Chorus micro-kernel operating system environment which provides the necessary soft real-time support while simultaneously running conventional applications. Our approach is to extend existing Chorus abstractions to include QoS configurability, connection oriented communications and real-time threads. The paper defines a low level API for distributed real-time programming and describes an implementation which features a close integration of communications and thread scheduling and the use of a split level scheduling architecture with kernel and user level threads.

<I>Responsive Multithreaded (RMT) Processor</I> is designed for distributed real-time systems. This paper focuses on the multimedia processing architecture of <I>RMT Processor</I>. Multimedia processing requires high-throughput calculation for bulky data processing. <I>RMT Processor</I> architecture is based on eight-way prioritized simultaneous multithreading, which executes each thread in order of priority. Since the priority of hard real-time threads is higher than that of multimedia processing threads, instruction issue slots used by the multimedia processing threads are few in <I>RMT Processor</I> when hard real-time threads are executed simultaneously. Therefore multimedia processing threads need to utilize instruction issue slots effectively to achieve high performance. We have designed a novel vector operation mechanism to process multimedia data efficiently in parallel. Because the same instructions are iterated in multimedia processing, the compound operation mechanism is designed to calculate more data per instruction in multimedia processing.

This paper addresses the problem of how to schedule periodic, real-time threads on a class of architectures referred, to as multilevel-context (MLC) architectures. Examples of such architectures are real-time operating systems with support for user- or kernel-level threads, and multithreaded microprocessors endowed with on-chip contexts. A common feature of these architectures is that they provide support for the administration of threads within contexts at different levels of abstraction. Therefore, the cost for switching between threads will depend on the affinity of their corresponding contexts. The main contributions of this paper are to demonstrate (i) how the scheduling performance for off-line scheduling on MLC architectures can benefit from an integrated heuristic that is cognizant of both the time-criticality of a thread and the current context affinity; and (ii) how the predicted performance for on-line scheduling on MLC architectures can benefit from an off-line schedulability test that accounts for variations in the context affinity.

There is wide agreement that one of the most important impediments to the performance of current and future pipelined superscalar processors is the presence of conditional branches in the instruction stream. Speculative execution seems to be one solution of choice to the branch problem, but speculative work is discarded if a branch is mispredicted. Therefore, we need a very accurate branch predictor; 95% accuracy is not good enough. This paper proposes branch classification to help improve the accuracy of branch predictors. Branch classification allows an individual branch instruction to be associated with the branch predictor best suited to predict its direction. Using this approach, a hybrid branch predictor can be constructed such that each component branch predictor predicts those branches for which it is best suited. This paper suggests one classification scheme, analyzes several branch predictors, and proposes a hybrid branch predictor that achieves higher prediction accuracy than any branch predictor previously reported in the literature.

Pipeline stalls due to conditional branches represent one of the most significant impediments to realizing the performance potential of deeply pipelined, superscalar processors. Many branch predictors have been proposed to help alleviate this problem, including the Two-Level Adaptive Branch Predictor, and more recently, two-component hybrid branch predictors.In a less idealized environment, such as a time-shared system, code of interest involves context switches. Context switches, even at fairly large intervals, can seriously degrade the performance of many of the most accurate branch prediction schemes. In this paper, we introduce a new hybrid branch predictor and show that it is more accurate (for a given cost) than any previously published scheme, especially if the branch histories are periodically flushed due to the presence of context switches.

Pipeline stalls due to conditional branches represent one of the most significant impediments to realizing the performance potential of deeply pipelined, superscalar processors. Many branch predictors have been proposed to help alleviate this problem, including the Two-Level Adaptive Branch Predictor, and more recently, two-component hybrid branch predictors.In a less idealized environment, such as a time-shared system, code of interest involves context switches. Context switches, even at fairly large intervals, can seriously degrade the performance of many of the most accurate branch prediction schemes. In this paper, we introduce a new hybrid branch predictor and show that it is more accurate (for a given cost) than any previously published scheme, especially if the branch histories are periodically flushed due to the presence of context switches.

The Precomputed-Branch architecture: Efficient branches with compiler support

Modern wide-issue superscalar processors tend to adopt deeper pipelines in order to attain high clock rates. This trend increases the number of on-the-fly instructions in processors and a mispredicted branch can result in substantial amounts of wasted work. In order to mitigate these wasted works, an accurate branch prediction is required for the high performance processors. In order to improve the prediction accuracy, we propose the bimode++ branch predictor. It is an enhanced version of the bimode branch predictor. Throughout execution from the start to the end of a program, some branch instructions have the same result at all times. These branches are defined as extremely biased branches. The bimode++ branch predictor is unique in predicting the output of an extremely biased branch with a simple hardware structure. In addition, the bimode++ branch predictor improves the accuracy using the refined indexing and a fusion function. Our experimental results with benchmarks from SpecFP, SpecINT, multi-media and server area show that the bimode++ branch predictor can reduce the misprediction rate by 13.2% to the bimode and by 32.5% to the gshare.

Branch misprediction is one of the important causes of performance degradation in superpipelined and superscalar processors. Most of the existing branch predictors, based on the exploiting of branch history, suffer from prediction accuracy decrease caused by frequent context switches. The goal of this research is to reduce misprediction rate (MPR) when the context switches are frequent, and not to increase the MPR when the context switches are relatively rare. We propose two independent, but closely related modifications of global adaptive prediction mechanisms: first, to flush only the branch history register (BHR) at context switch, instead of reinitialization of the whole predictor, and second, to use two separated BHRs, one for user and one for kernel branches, instead of one global history register. We have evaluated the ideas by measurements on real traces from IBS (Instruction Benchmark Set), and have shown that both modifications reduce MPR at negligible hardware cost.

High-performance superscalar processors, which can be used in building base-stations of cell phones and cloud-based web servers, rely heavily on aggressive branch predictors to avoid stalls no matter the branch is taken or not. Dynamic branch predictor which is based on the historical records of the previously executed branches always outputs good performance. Two-bit predictor discussed in this paper is one of the most popular ones that always practically employed. This paper demonstrates two implementations of two-bit predictors. Using BTB to process solo conditional branches is the first one, which is normally used. Other categories of branch instructions may results in several bubbles as the penalty. While the other implementation employs BTB dealing with all kinds of branch instructions, generating target addresses without any delay cycle. Simulation results show that the second implementation has much better performance than the former one. It decreases the mis-prediction rate from 12.26% to 11.48%, and also has much higher prediction accuracy on indirect jumps. With these results, we have our predictor re-designed accordingly and implemented successfully in superscalar processors.

A basic rule in computer architecture is that a processor cannot execute an application faster than it fetches its instructions. This paper presents a novel cost-effective mechanism called the two-block ahead branch predictor. Information from the current instruction block is not used for predicting the address of the next instruction block, but rather for predicting the block following the next instruction block.This approach overcomes the instruction fetch bottle-neck exhibited by wide-dispatch brainiac processors by enabling them to efficiently predict addresses of two instruction blocks in a single cycle. Furthermore, pipelining the branch prediction process can also be done by means of our predictor for speed demon processors to achieve higher clock rate or to improve the prediction accuracy by means of bigger prediction structures.Moreover, and unlike the previously-proposed multiple predictor schemes, multiple-block ahead branch predictors can use any of the branch prediction schemes to perform the very accurate predictions required to achieve high-performance on superscalar processors.

In the push for ever increasing performance out of processor architectures, there is a need to expand beyond the limitations of existing scalar approaches. Superscalar architectures provide one such means. By dynamically executing more than one instruction per clock cycle, superscalar architectures can improve performance without relying solely on technology improvements for these gains. This paper examines a new technique for superscalar control implementation, called the schedule table. The schedule table facilitates dependency checking, out of order instruction issue, out of order execution, branch prediction, speculative execution, precise interrupts, and fast and efficient misprediction recovery.

The techniques of pipelining, superscalar execution, and branch prediction used in the Pentium CPU, which integrates 3.1 million transistors in 0.8- mu m BiCMOS technology, are described. The technology improvements associated with the three most recent microprocessor generations are outlined. The Pentium's compatibility, performance, organization, and development process are also described. The compiler technology developed with the Pentium microprocessor, which includes machine-independent optimizations common to current high-performance compilers, such as inlining, unrolling, and other loop transformations, is reviewed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Modern processors usually have a deep pipeline, superscalar architecture to obtain higher performance. As pipelines are getting deeper, accurate branch prediction is critical to achieve high performance, since fetched instructions after a branch have to be flushed from inside the pipeline when the prediction is wrong. This paper studies the performance of several types of branch predictors, starting from local branch predictor and global branch predictor. Simulation results show that the global history predictor outperforms the local history predictor due to the characteristic that branches tend to be correlated. However, the global history predictor still suffers an aliasing problem that degrades performance. Four techniques are proposed to alleviate the aliasing problem. The performance is evaluated by using Simplescalar with SPEC CINT95 benchmark programs. The proposed predictors display better performance over the conventional predictors after careful configuration of each.

Branch prediction is one of the main hurdles in the roadmap towards deeper pipelines and higher clock frequencies. This work presents a new approach to enhancing current branch predictors: Selective Branch Prediction Reversal. The rationale behind this proposal is the fact that many branch mispredictions can be avoided if branch prediction is selectively reversed. We present a Branch Prediction Reversal Unit (BPRU) that selectively reverses branch predictions by correlating with the predicted values of the branch inputs, in addition to recent control flow. As a case study, we have included the BPRU in an already proposed branch predictor, the Branch Predictor through Value Prediction (BPVP). The effect is a reduction by half in its original misprediction rate. We have also measured the improvement when the BPRU engine is used in a hybrid scheme composed of a BPVP and a gshare predictor. Results using immediate updates show average reductions in misprediction rate ranging from 7% to 14%. Performance evaluation of the proposed BPRU in a 20-stage superscalar processor shows an IPC improvement of up to 9%.