The authors consider whether SPECmarks, the figures of merit obtained from running the SPEC benchmarks under certain specified conditions, accurately indicate the performance to be expected from real, live work loads. Miss ratios for the entire set of SPEC92 benchmarks are measured. It is found that instruction cache miss ratios in general, and data cache miss ratios for the integer benchmarks, are quite low. Data cache miss ratios for the floating-point benchmarks are more in line with published measurements for real work loads.

We describe the Slice Processor micro-architecture that implements a generalized operation-based prefetching mechanism. Operation-based prefetchers predict the series of operations, or the computation slice that can be used to calculate forthcoming memory references. This is in contrast to outcome-based predictors that exploit regularities in the (address) outcome stream. Slice processors are a generalization of existing operation-based prefetching mechanisms such as stream buffers where the operation itself is fixed in the design (e.g., address + stride). A slice processor dynamically identifies frequently missing loads and extracts on-the-fly the relevant address computation slices. Such slices are then executed in-parallel with the main sequential thread prefetching memory data. We describe the various support structures and emphasize the design of the slice detection mechanism. We demonstrate that a relatively simple organization can significantly improve performance over an aggressive, dynamically-scheduled processor and for a set of pointer-intensive programs and for some integer applications from the SPEC'95 suite. In particular, a slice processor that can detect slices of up to 8 instructions extracted over of a region of up to 32 instructions improves performance by 11% on the average (even if slice detection requires up to 32 cycles). Allowing slices of up to 16 instructions results in an average performance improvement of 15%. Finally, we study how our operation-based predictor interacts with an outcome-based one and find them mutually beneficial.

In this paper, we consider hardware-based scanning and analyzing packets payload in order to detect hazardous contents. We present two pattern matching techniques to compare incoming packets against intrusion detection search patterns. The first approach, decoded partial CAM (DpCAM), predecodes incoming characters, aligns the decoded data, and performs logical and on them to produce the match signal for each pattern. The second approach, perfect hashing memory (PHmem), uses perfect hashing to determine a unique memory location that contains the search pattern and a comparison between incoming data and memory output to determine the match. Both techniques are well suited for reconfigurable logic and match about 2200 intrusion detection patterns using a single Virtex2 field-programmable gate-array device. We show that DpCAM achieves a throughput between 2 and 8 Gb/s requiring 0.58-2.57 logic cells per search character. On the other hand, PHmem designs can support 2-5.7 Gb/s using a few tens of block RAMs (630-1404 kb) and only 0.28-0.65 logic cells per character. We evaluate both approaches in terms of performance and area cost and analyze their efficiency, scalability, and tradeoffs. Finally, we show that our designs achieve at least 30% higher efficiency compared to previous work, measured in throughput per area required per search character.

Billion transistor systems-on-chip increasingly require dynamic management of their hardware components and careful coordination of the tasks that they carry out. Diverse real-time monitoring functions assist towards this objective through the collection of important system metrics, such as throughput of processing elements, communication latency, or resource utilization for each application. The online evaluation of these metrics can result in localized or global decisions that attempt to improve aspects of system behavior, system performance, quality-of-service, power and thermal effects under nominal conditions. This work provides a comprehensive categorization of monitoring approaches used in multiprocessor SoCs. As adaptive systems are encountered in many disciplines, it is imperative to present the prominent research efforts in developing online monitoring methods. To this end we offer a taxonomy that groups strongly related techniques that designers increasingly use to produce more efficient and adaptive chips. The provided classification helps to understand and compare architectural mechanisms that can be used in systems, while one can envisage the innovations required to build real adaptive and intelligent systems-on-chip.