To alleviate high energy dissipation of unnecessary snooping accesses, snoop filters have been designed to reduce snoop lookups. These filters have the problem of decreasing filtering efficiency, and thus usually rely on partial or whole filter reset by detecting block evictions. Unfortunately, the reset conditions occur infrequently or unevenly (called passive filter deletion ). This work proposes the concept of revitalized snoop filter (RSF) design, which can actively renew the destination filter by employing a generation wrapping-around scheme for various reference behaviors. We further utilize a sampling mechanism for RSF to timely trigger precise filter revitalizations, so that unnecessary RSF flushing can be minimized. The proposed RSF can be integrated to various existent inclusive snoop filters with only a minor change to their designs. We evaluate our proposed design and demonstrate that RSF eliminates 58.6% of snoop energy compared to JETTY on average while inducing only 6.5% of revitalization energy overhead. In addition, RSF eliminates 45.5% of snoop energy compared to stream registers on average and only induces 2.5% of revitalization energy overhead. Overall, these RSFs reduce the total L2 cache energy consumption by 52.1% (58.6% -- 6.5%) as compared to JETTY and by 43% (45.5% -- 2.5%) as compared to stream registers. Furthermore, RSF improves the overall performance by 1% to 1.4% on average compared to JETTY and stream registers for various benchmark suites.

Ternary content-addressable memory (TCAM)-based search engines generally need a priority encoder (PE) to select the highest priority match entry for resolving the multiple match problem due to the don't care (X) features of TCAM. In contemporary network security, TCAM-based search engines are widely used in regular expression matching across multiple packets to protect against attacks, such as by viruses and spam. However, the use of PE results in increased energy consumption for pattern updates and search operations. Instead of using PEs to determine the match, our solution is a three-phase search operation that utilizes the length information of the matched patterns to decide the longest pattern match data. This paper proposes a promising memory technology called priority-decision in memory (PDM), which eliminates the need for PEs and removes restrictions on ordering, implying that patterns can be stored in an arbitrary order without sorting their lengths. Moreover, we present a sequential input-state (SIS) scheme to disable the mass of redundant search operations in state segments on the basis of an analysis distribution of hex signatures in a virus database. Experimental results demonstrate that the PDM-based technology can improve update energy consumption of nonvolatile TCAM (nvTCAM) search engines by 36%-67%, because most of the energy in these search engines is used to reorder. By adopting the SIS-based method to avoid unnecessary search operations in a TCAM array, the search energy reduction is around 64% of nvTCAM search engines.

In a modern system-on-chip design, hundreds of cores and intellectual properties can be integrated into a single chip. To be suitable for high-performance interconnects, designers increasingly adopt advanced interconnect protocols that support novel mechanisms of parallel accessing, including outstanding transactions and out-of-order completion of transactions. To implement those novel mechanisms, a master tags an ID to each transaction to decide in-order or out-of-order properties. However, these advanced protocols may lead to transaction deadlocks that do not occur in traditional protocols. To prevent the deadlock problem, current solutions stall suspicious transactions and in certain cases, many such stalls can incur serious performance penalty. In this brief, we propose a novel ID assignment mechanism that guarantees the issued transactions to be deadlock-free and results in significant reduction in the number of transaction stalls issued by masters. Our experimental results show encouraging performance improvements compared with previous works with little hardware and power overheads.

TCAM-based search engines are widely used in regular expression matching across multiple packets. However, the use of priority encoder results in increased energy consumption of pattern updates and search operations. This work, proposes a promising memory technology, called Priority-Decision in Memory (PDM), which eliminates the need for priority encoders and removes restrictions on ordering, meaning that patterns can be stored in an arbitrary order without sorting their lengths. Moreover, we present a Sequential Input-State Search (SIS) scheme to disable the mass of redundant search operations in state segments, based on the analysis distribution of hex signatures in a virus database. Experimental results demonstrate that PDM-based technology can improve update energy consumption of nvTCAM search engines by 36%~67% because most of the energy in the latter is used to reorder. By adopting the SIS-based method to avoid unnecessarily search operations in a TCAM array, the search energy reduction is around 64% of nvTCAM search engines.

Soft error has become an important reliability issue in advanced technologies. To tolerate soft errors, solutions suggested in previous works incur significant performance and power penalties, especially when a design with fault-tolerant structures is overprotected. In this paper, we present a soft-error-tolerant design methodology to tradeoff performance, power, and reliability for different applications. First, four novel detection and correction flip-flop (FF) structures are proposed to provide different levels of tolerance capability against soft errors. Second, architecture-level vulnerability and logic-level susceptibility analyses are employed to identify weak FFs that can easily cause program execution errors. Third, an optimization framework is developed to synthesize the proposed four novel FF structures into weak and highly observable storage bits with the flexibility of trading off performance, power, and reliability. A five-stage pipeline RISC core (UniRISC) is adopted to demonstrate the usefulness of our methodology. Experimental results show that the proposed method can accomplish design goals by balancing performance, power, and reliability. For example, we can not only satisfy the reliability requirement that no more than five errors occur per one billion hours in a design but also reduce up to 87% performance overhead and 91% power overhead when compared with previous works.

NVM has commonly been used to address increasingly large last-level caches (LLCs) requirements by reducing leakage. However, frequent data-writing operations result in increased energy consumption. In this context, a promising memory technology, Non-volatile SRAM (nvSRAM), enables normal and standby operation modes which can be used to store various types of data. However, nvSRAM suffers from high dynamic energy usage due to frequent switching between operation modes. In this paper, we propose a redundant store elimination (RSE) scheme which, on average, discards 94% of needless bit-write operations. Moreover, we present a retention-aware cache management policy to reduce data updates of cache blocks, based on the correlation between data lifetime and cache types. Experimental results demonstrate that our proposal can improve energy consumption of SRAM-based and RRAM-based LLCs by 57% and 31%, respectively.

Dalvik virtual machine in the Android system creates a profiling barrier between VM-space applications and Linux user-space libraries. It is difficult for existing profiling tools on the Android system to definitively identify whether a bottleneck occurred in the application level, the Linux user-space level, or the Linux kernel level. Information barriers exist between VM-space applications and Linux native analysis tools due to runtime virtual machines' dynamic memory allocation mechanism. Furthermore, traditional vertical profiling tools targeted for Java virtual machines cannot be simply applied on the Dalvik virtual machine due to its unique design. The proposed the Reconfigurable Vertical Profiling Framework bridges the information gap and streamlines the hardware-software co-design process for the Android runtime system.