A Storage-Effective BTB Organization for Servers

The Precomputed-Branch architecture: Efficient branches with compiler support

Using cache-like architectural components including data caches, instruction caches, or branch target buffers as a side channel, software cache-based side-channel attacks are able to derive secret keys used in cryptographic operations through legitimate software activities. Existing software solutions are typically application specific and incur substantial performance overhead. Recent hardware proposals against attacks on data caches, although effective in reducing performance overhead, may still be vulnerable to advanced attacks. Furthermore, efficient defenses against attacks on other cache structures, including instruction caches and branch target buffers, are missing. In this paper, we propose hardware-software integrated approaches to defend against software cache-based attacks comprehensively. For attacks on data caches, we propose to use preloading, informing loads, and informing loads with software random permutation to secure the partition-locked cache (PLcache), the random permutation (RPcache) and regular caches, respectively. These approaches present different tradeoffs between hardware complexity and performance overhead. To defend against attacks on instruction caches, we show that the PLcache with preloading and the RPcache provide good protection. To defend against attacks based on branch target buffers, we propose to adopt a new update policy to eliminate potential information leaking. Our experiments show that the proposed schemes not only provide strong security protection but also incur small performance overhead.

With increasing use of runtime polymorphism and reliance on runtime type interpretation, the presence and importance of indirect branches has seen a considerable rise in recent workloads. Evidently, accurate target prediction for indirect branches has emerged as an important problem. While direction prediction of direct branches has received considerable research attention leading to efficient prediction policies and hardware structures implemented inside modern processors, proposals for target prediction for indirect branches has been relatively few. The problem of accurate target prediction for indirect branches is significantly tough since these transfer control to an address stored in a register that is known only at runtime. Unlike conditional direct branches, indirect branches can have more than two targets to be resolved at runtime, for which prediction requires a full 32-bit / 64-bit address to be predicted, in contrast to just a taken or not-taken decision as needed for direction prediction of direct branches. Recent research shows indirect branches, being mispredicted more frequently, can start to dominate the overall branch misprediction cost. In modern processors, the only hardware structure available to facilitate target address prediction for indirect branches is a fixed-size Branch Target Buffer (BTB). BTB is often designed as a set associative cache for storing recent target addresses for branch instructions encountered during execution, with a motivation of being able to reuse the same addresses for future instances, thereby saving latency cycles. Evidently, designing efficient indexing schemes and replacement mechanisms for BTB structures is crucial, more so, for indirect branches, since these serve as the only prediction handle. In this paper, our objective is to examine a hierarchical BTB design for multicores with total size comparable to what exists today, with a motivation towards possible improvement of prediction accuracy by facilitating collaborative constructive learning between programs executing in different cores that encounter similar histories. Specifically, we wish to propose the concept of a small on-chip L1 BTB inside each core, supported by a larger off-chip L2 BTB shared among the cores. Our motivation towards a hierarchical BTB design is twofold. On one hand, in a multiprogramming environment, where the same program is executed in multiple cores, on different test cases, there is a significant potential of target information reuse for indirect branches, as is evident from our experiments on SPEC 2006 workloads. This is typically useful for machine learning based workloads where the training phase is often executed in different cores with the same neural network being trained on different training sets. On the other hand, with different programs in different cores, there is some chance of reuse as well, due to sharing of system libraries. The essence of our idea rests on the fact that programs executed in different cores have similar history patterns that can similarly influence the target addresses. Our design aims to decrease on the on-chip L1 BTB size while investing more storage for the off-chip shared L2 BTB. Suitable allocation and replacement policies support our hierarchical design. Initial experiments show expected accuracy benefits.

A Branch Target Buffer (BTB) is a mechanism to support speculative execution in order to overcome the performance penalty caused by branch instructions in pipelined microprocessors. Being an intrinsically fault tolerant unit, it is hard to achieve a good fault coverage resorting to plain functional testing methods. In this paper we analyze the causes for low functional testability and propose some techniques able to effectively face these issues. In particular, we describe a strategy to perform SBST on fully associative BTB units. The unit's general structure is analyzed, a suitable test program is proposed and the strategy to observe the test responses is explained. Feasibility and effectiveness of the proposed approach are shown on a MIPS-like processor.

Applying stack simulation for branch target buffers

Indirect-branch prediction is becoming more important for modern processors as more programs are written in object-oriented languages. Previous hardware-based indirect-branch predictors generally require significant hardware storage or use aggressive algorithms which make the processor front-end more complex. In this paper, we propose a fast and cost-efficient indirect-branch prediction strategy, called Target Address Pointer (TAP) Prediction. TAP Prediction reuses the history-based branch direction predictor to detect occurrences of indirect branches, and then stores indirect-branch targets in the Branch Target Buffer (BTB). The key idea of TAP Prediction is to predict the Target Address Pointers, which generate virtual addresses to index the targets stored in the BTB, rather than to predict the indirect-branch targets directly. TAP Prediction also reuses the branch direction predictor to construct several small predictors. When fetching an indirect branch, these small predictors work in parallel to generate the target address pointer. Then TAP prediction accesses the BTB to fetch the predicted indirect-branch target using the generated virtual address. This mechanism could achieve time cost comparable to that of dedicated-storage-predictors, without requiring additional large amounts of storage. Our evaluation shows that for three representative direction predictors-Hybrid, Perceptrons, and O-GEHL-TAP schemes improve performance by 18.19%, 21.52%, and 20.59%, respectively, over the baseline processor with the most commonly-used BTB prediction. Compared with previous hardware-based indirect-branch predictors, the TAP-Perceptrons scheme achieves performance improvement equivalent to that provided by a 48KB TTC predictor, and it also outperforms the VPC predictor by 14.02%.

Electronic systems are increasingly used for safety-critical applications, where the effects of faults must be taken under control and hopefully avoided. For this purpose, test of manufactured devices is particularly important, both at the end of the production line and during the operational phase. This paper describes a method to test the logic implementing the Branch Prediction Unit in pipelined and superscalar processors when this follows the Branch Target Buffer (BTB) architecture; the proposed approach is functional, i.e., it is based on forcing the processor to execute a suitably devised test program and observing the produced results. Experimental results are provided on the DLX processor, showing that the method can achieve a high value of stuck-at fault coverage while also testing the memory in the BTB.

Instruction fetch behavior has been shown to be very regular and predictable, even for diverse application areas. In this work, we propose the Lookahead Instruction Fetch Engine (LIFE), which is designed to exploit the regularity present in instruction fetch. The nucleus of LIFE is the Tagless Hit Instruction Cache (TH-IC), a small cache that assists the instruction fetch pipeline stage as it efficiently captures information about both sequential and non-sequential transitions between instructions. TH-IC provides a considerable savings in fetch energy without incurring the performance penalty normally associated with small filter instruction caches. LIFE extends TH-IC by making use of advanced control flow metadata to further improve utilization of fetch-associated structures such as the branch predictor, branch target buffer, and return address stack. These structures are selectively disabled by LIFE when it can be determined that they are unnecessary for the following instruction to be fetched. Our results show that LIFE enables further reductions in total processor energy consumption with no impact on application execution times even for the most aggressive power-saving configuration. We also explore the use of LIFE metadata on guiding decisions further down the pipeline. Next sequential line prefetch for the data cache can be enhanced by only prefetching when the triggering instruction has been previously accessed in the TH-IC. This strategy reduces the number of useless prefetches and thus contributes to improving overall processor efficiency. LIFE enables designers to boost instruction fetch efficiency by reducing energy cost without negatively affecting performance.

We present an efficient cache scheme, which can considerably reduce instruction cache misses caused by procedure call/returns. This scheme employs N-way banks and XOR mapping functions. The main function of this scheme is to place a group of instructions separated by a call instruction into a bank according to the initial and final bank selection mechanisms. After the initial bank selection mechanism selects a bank on an instruction cache miss, the final bank selection mechanism will determine the final bank for updating a cache line as a correction mechanism. These two mechanisms can guarantee that recent groups of instructions exist in each bank safely. We have developed a simulation program by using Shade and Spixtools, provided by SUN Microsystems, on an ultra SPARC/10 processor. Our experimental results show that these schemes reduce conflict misses more effectively than skewed-associative caches in both C (up to 9.29% improvement) and C++ (up to 30.71% improvement) programs on L1 caches. In addition, they also allow for a significant miss reduction on Branch Target Buffers (BTB).

There is a growing need for accurate power models at the system level. Memory structures such as caches, Branch Target Buffers (BTBs), and register files occupy significant area in contemporary SoC designs and are the main contributors to system leakage power dissipation. Existing models for leakage power estimation in array structures typically use coefficients derived from elaborate SPICE simulations. However, these methodologies are not applicable to array designs in a newer technology, that require power estimates early in the design cycle. In this paper, we propose analytical models for array structures that are based only on high level design parameters. Assuming typical circuit implementation styles, we identify the transistors that contribute to the leakage power in each array sub-circuit and develop models as a function of the operation (read/write/idle) on the array and organizational parameters of the array. The developed models are validated by comparing their estimates against the leakage power measured using SPICE simulations on industrial array designs belonging to the e5001 processor core. The comparison shows that the models are accurate with an error margin of less than 21.5% and thus can be used in high-level power-performance exploration. Interestingly, in array designs with dual threshold voltage technology, we observed that contrary to the general expectation, the array memory core contributes to just 9% and the address decoder contributes to as much as 62% of the total leakage power.

Designing a modern microprocessor is a complex task that demands careful balance between cycle time, cycle-per-instruction and area costs. In particular, the instruction fetch unit greatly affects the performance of a multi-issue processor. It must provide adequate bandwidth to sustain peak instruction issue rate and must predict future instruction sequences with high accuracy. In the UltraSPARC prefetch and dispatch unit design, we examined a technique that combined two prediction methods: predictive set-associative cache and in-cache prediction. This combination was compared with alternative designs such as direct-mapped and set-associative caches, and a branch history table and a branch target buffer. We chose the combined prediction technique for its fast cycle time, lower cycle-per-instruction, and lower area costs. This paper summarizes the trade-off decisions made in the design of the UltraSPARC instruction prefetch and dispatch unit.

As the pipeline length increases, the accuracy in a branch prediction gets critical to overall performance. In designing a branch predictor, in addition to accuracy, microarchitects should consider power consumption, especially in embedded processors. In this paper, we propose a low power branch predictor, which is based on the gshare predictor, by accessing the BTB (Branch Target Buffer) only when the prediction from the PHT (Prediction History Table) is taken. To enable this, the PHT is accessed one cycle earlier to prevent the additional delay. As a side effect, two predictions from the PHT are obtained at one access to the PHT, which leads to more power reduction. The proposed branch predictor reduces the power consumption, not requiring any additional storage arrays, not incurring additional delay (except just one MUX delay) and never harming accuracy. The simulation results show that the proposed predictor reduces the power consumption by 43-52%.KeywordsPower ConsumptionPower ReductionTotal Power ConsumptionAdditional DelayEmbed ProcessorThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

We have designed a DLX-based superscalar processor simulator. This simulator provides many more functions than its predecessors developed elsewhere. We have added trap handlers and required C functions in the system so that most of the SPEC92 programs now run on the simulator. In addition, this simulator is fully configurable and re-configurable. Specifically, the following options and functions are provided by the simulator.• Central window versus distributed reservation stations.• Branch prediction mechanisms using static or dynamic schemes. The later provides branch target buffer and branch history table.• Configurable functional units.• A fully configurable KNL non-blocking cache structure incorporated int he simulator. (K: the number of ways. N: the number of cache lines in a way. L: line size). Split versus unified option and cm + βmL/D memory latency model.• Better debugging functions allowing the interruption of the simulation, reconfiguration, restart in a cycle-by-cycle fashion, or run to the end.• NT/Win95 platform ready.This DLX-based superscalar simulator is instruction-driven, which offers richer educational features than most of the trace-driven simulators. For information about this simulator, please refer to http://com.el.yuntech.edu.tw.

This paper presents a branch prediction algorithm and a 4-way set-associative cache for performance improvement of 32-bit RISC processor and a clock gating algorithm using ODC (observability don't care) operation for a low-power processor. The branch prediction algorithm has a structure using BTB (branch target buffer) and 4-way set associative cache using pseudo LRU (least recently used) algorithm. The proposed algorithm is applied to OpenRISC1200 processor, embedded processor and implemented on Xilinx VIRTEX-4 XC4VLX80 FPGA device and the FPGA executes at the maximum frequency of 53.042MHz. As a result of estimation of performance and dynamic power, the performance of the OpenRISC1200 processor using the proposed algorithm is improved about 5~9% and dynamic power of the processor using Samsung 0.18 mum technology library is reduced by 13.9%.

This uses Wattch and the SPEC 2000 integer and floating-point benchmarks to explore the role of branch predictor organization in power/energy/performance trade offs for processor design. Even though the direction predictor by itself represents less than 1 percent of the processor's total power dissipation, prediction accuracy is nevertheless a powerful lever on processor behavior and program execution time. A thorough study of branch predictor organizations shows that, as a general rule, to reduce overall energy consumption in the processor, it is worthwhile to spend more power in the branch predictor if this results in more accurate predictions that improve running time. This not only improves performance, but can also improve the energy-delay product by up to 20 percent. Three techniques, however, can reduce power dissipation without harming accuracy. Banking reduces the portion of the branch predictor that is active at any one time. A new on-chip structure, the prediction probe detector (PPD), uses predecode bits to entirely eliminate unnecessary predictor and branch target buffer (BTB) accesses. Despite the extra power that must be spent accessing it, the PPD reduces local predictor power and energy dissipation by about 31 percent and overall processor power and energy dissipation by 3 percent. These savings can be further improved by using profiling to annotate branches, identifying those that are highly biased and do not require static prediction. Finally, we explore the effectiveness of a previously proposed technique, pipeline gating, and find that, even with adaptive control based on recent predictor accuracy, pipeline gating yields little or no energy savings.