Commercial applications such as databases and Web servers constitute the largest and fastest-growing segment of the market for multiprocessor servers. Ongoing innovations in disk subsystems, along with the ever increasing gap between processor and memory speeds, have elevated memory system design as the critical performance factor for such workloads. However, most current server designs have been optimized to perform well on scientific and engineering workloads, potentially leading to design decisions that are non-ideal for commercial applications. The above problem is exacerbated by the lack of information on the performance requirements of commercial workloads, the lack of available applications for widespread study, and the fact that most representative applications are too large and complex to serve as suitable benchmarks for evaluating trade-offs in the design of processors and servers. This paper presents a detailed performance study of three important classes of commercial workloads: online transaction processing (OLTP), decision support systems (DSS), and Web index search. We use the Oracle commercial database engine for our OLTP and DSS workloads, and the AltaVista search engine for our Web index search workload. This study characterizes the memory system behavior of these workloads through a large number of architectural experiments on Alpha multiprocessors augmented with full system simulations to determine the impact of architectural trends. We also identify a set of simplifications that make these workloads more amenable to monitoring and simulation without affecting representative memory system behavior. We observe that systems optimized for OLTP versus DSS and index search workloads may lead to diverging designs, specifically in the size and speed requirements for off-chip caches. 1

The microprocessor industry is currently struggling with higher development costs and longer design times that arise from exceedingly complex processors that are pushing the limits of instructionlevel parallelism. Meanwhile, such designs are especially ill suited for important commercial applications, such as on-line transaction processing (OLTP), which suffer from large memory stall times and exhibit little instruction-level parallelism. Given that commercial applications constitute by far the most important market for high-performance servers, the above trends emphasize the need to consider alternative processor designs that specifically target such workloads. The abundance of explicit thread-level parallelism in commercial workloads, along with advances in semiconductor integration density, identify chip multiprocessing (CMP) as potentially the most promising approach for designing processors

Recent high-performance processors employ sophisticated techniques to overlap and simultaneously execute multiple computation and memory operations. Intuitively, these techniques should help database applications, which are becoming increasingly compute and memory bound. Unfortunately, recent studies report that they do not improve database system performance to the same extent as scientific workloads. Recent work on database systems focusing on minimizing memory latencies, such as cache-conscious algorithms for sorting and data placement, is one step toward addressing this problem. However, to best design high performance DBMSs, we must carefully evaluate and understand the processor and memory behavior of commercial DBMSs on today’s hardware platforms. In this paper we answer the question "Where does time go when a database system executes on a modern computer platform? " We examine four commercial DBMSs running on an Intel Xeon and NT 4.0. We introduce a framework for analyzing query execution time on a DBMS running on a server with a modern processor and memory architecture. To focus on processor and memory interactions and exclude effects from the I/O subsystem, we use a memory resident database. Using simple queues, we find that database developers should (a) optimize data placement for the second level of data cache, and not the first, (b) optimize instruction placement to reduce first-level instruction cache stalls, but (c) not expect the overall execution time to decrease significantly without addressing stalls related to subtle implementation issues (e.g., branch prediction). 1

Chip multiprocessor (CMP) systems have made the on-chip caches a critical resource shared among co-scheduled threads. Limited off-chip bandwidth, increasing on-chip wire delay, destructive inter-thread interference, and diverse workload characteristics pose key design challenges. To address these challenge, we propose CMP cooperative caching (CC), a unified framework to efficiently organize and manage on-chip cache resources. By forming a globally managed, shared cache using cooperative private caches. CC can effectively support two important caching applications: (1) reduction of average memory access latency and (2) isolation of destructive inter-thread interference. CC reduces the average memory access latency by balancing between cache latency and capacity opti-mizations. Based private caches, CC naturally exploits their access latency benefits. To improve the effective cache capacity, CC forms a “shared ” cache using replication control and LRU-based global replacement policies. Via cooperation throttling, CC provides a spectrum of caching behaviors between the two extremes of private and shared caches, thus enabling dynamic adaptation to suit workload requirements. We show that CC can achieve a robust performance advantage over private and shared cache schemes across different processor, cache and memory configurations, and a wide selection of multithreaded and multiprogrammed

Relational database systems have traditionally optimzed for I/O performance and organized records sequentially on disk pages using the N-ary Storage Model (NSM) (a.k.a., slotted pages). Recent research, however, indicates that cache utilization and performance is becoming increasingly important on modern platforms. In this paper, we first demonstrate that in-page data placement is the key to high cache performance and that NSM exhibits low cache utilization on modern platforms. Next, we propose a new data organization model called PAX (Partition Attributes Across), that significantly improves cache performance by grouping together all values of each attribute within each page. Because PAX only affects layout inside the pages, it incurs no storage penalty and does not affect I/O behavior. According to our experimental results, when compared to NSM (a) PAX exhibits superior cache and memory bandwidth utilization, saving at least 75% of NSM's stall time due to data cache accesses, (b) range selection queries and updates on memoryresident relations execute 17-25% faster, and (c) TPC-H queries involving I/O execute 11-48% faster.

Database applications such as online transaction processing (OLTP) and decision support systems (DSS) constitute the largest and fastest-growing segment of the market for multiprocessor servers. However, most current system designs have been optimized to perform well on scientific and engineering workloads. Given the radically different behavior of database workloads (especially OLTP), it is important to re-evaluate key system design decisions in the context of this important class of applications. This paper examines the behavior of database workloads on shared-memory multiprocessors with aggressive out-of-order processors, and considers simple optimizations that can provide further performance improvements. Our study is based on detailed simulations of the Oracle commercial database engine. The results show that the combination of out-of-order execution and multiple instruction issue is indeed effective in improving performance of database workloads, providing gains of 1.5 and 2.6 t...

In this paper, we study the space of chip multiprocessor (CMP) organizations. We compare the area and performance trade-offs for CMP implementations to determine how many processing cores future server CMPs should have, whether the cores should have in-order or out-of-order issue, and how big the per-processor on-chip caches should be. We find that, contrary to some conventional wisdom, out-of-order processing cores will maximize job throughput on future CMPs. As technology shrinks, limited off-chip bandwidth will begin to curtail the number of cores that can be effective on a single die. Current projections show that the transistor/signal pin ratio will increase by a factor of 45 between 180 and 35 nanometer technologies. That disparity will force increases in per-processor cache capacities as technology shrinks, from 128KB at 100nm, to 256KB at 70nm, and to 1MB at 50 and 35nm, reducing the number of cores that would otherwise be possible.

The use of the Java programming language for implementing server-side application logic is increasing in popularity, yet there is very little known about the architectural requirements of this emerging commercial workload. We present a detailed characterization of the Transaction Processing Council’s TPC-W web benchmark, implemented in Java. The TPC-W benchmark is designed to exercise the web server and transaction processing system of a typical e-commerce web site. We have implemented TPC-W as a collection of Java servlets, and present an architectural study detailing the memory system and branch predictor behavior of the workload. We also evaluate the effectiveness of a coarse-grained multithreaded processor at increasing system throughput using TPC-W and other commercial workloads. We measure system throughput

This paper proposes and evaluates new synchronization schemes for a simultaneous multithreaded processor. We present a scalable mechanism that permits threads to cheaply synchronize within the processor, with blocked threads consuming no processor resources. We also introduce the concept of lock release prediction, which gains an additional improvement of 40%. Overall, we show that these improvements in synchronization cost enable parallelization of code that could not be effectively parallelized using traditional techniques. 1. Introduction The performance of a multiprocessor's synchronization mechanisms determine the granularity of parallelism that can be exploited on that machine. Synchronization on a conventional multiprocessor carries a high cost due to the hardware levels at which synchronization and communication must occur (e.g., main memory). As a result, compilers and programmers must decompose parallel applications in a coarse-grained way in order to reduce synchronization...

This paper presents the first analysis of operating system execution on a simultaneous multithreaded (SMT) processor. While SMT has been studied extensively over the past 6 years, previous research has focused entirely on user-mode execution. However, many of the applications most amenable to multithreading technologies spend a significant fraction of their time in kernel code. A full understanding of the behavior of such workloads therefore requires execution and measurement of the operating system, as well as the application itself. To carry out this study, we (1) modified the Digital Unix 4.0d operating system to run on an SMT CPU, and (2) integrated our SMT Alpha instruction set simulator into the SimOS simulator to provide an execution environment. For an OS-intensive workload, we ran the multithreaded Apache Web server on an 8-context SMT. We compared Apache's user- and kernel-mode behavior to a standard multiprogrammed SPECInt workload, and compared the SMT processor to an out-...