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

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Transactional memory (TM) simplifies parallel programming by guaranteeing that transactions appear to execute atomically and in isolation. Implementing these properties includes providing data version management for the simultaneous storage of both new (visible if the transaction commits) and old (retained if the transaction aborts) values. Most (hardware) TM systems leave old values “in place” (the target memory address) and buffer new values elsewhere until commit. This makes aborts fast, but penalizes (the much more frequent) commits. In this paper, we present a new implementation of transactional memory, Log-based Transactional Memory (LogTM), that makes commits fast by storing old values to a per-thread log in cacheable virtual memory and storing new values in place. LogTM makes two additional contributions. First, LogTM extends a MOESI directory protocol to enable both fast conflict detection on evicted blocks and fast commit (using lazy cleanup). Second, LogTM handles aborts in (library) software with little performance penalty. Evaluations running micro- and SPLASH-2 benchmarks on a 32way multiprocessor support our decision to optimize for commit by showing that only 1-2 % of transactions abort. 1.

In this paper we examine the problem of extending modern operating systems to run efficiently on large-scale shared memory multiprocessors without a large implementation effort. Our approach brings back an idea popular in the 1970s, virtual machine monitors. We use virtual machines to run multiple commodity operating systems on a scalable multiprocessor. This solution addresses many of the challenges facing the system software for these machines. We demonstrate our approach with a prototype called Disco that can run multiple copies of Silicon Graphics ’ IRIX operating system on a multiprocessor. Our experience shows that the overheads of the monitor are small and that the approach provides scalability as well as the ability to deal with the non-uniform memory access time of these systems. To reduce the memory overheads associated with running multiple operating systems, we have developed techniques where the virtual machines transparently share major data structures such as the program code and the file system buffer cache. We use the distributed system support of modern operating systems to export a partial single system image to the users. The overall solution achieves most of the benefits of operating systems customized for scalable multiprocessors yet it can be achieved with a significantly smaller implementation effort. 1

Serialization of threads due to critical sections is a fundamental bottleneck to achieving high performance in multithreaded programs. Dynamically, such serialization may be unnecessary because these critical sections could have safely executed concurrently without locks. Current processors cannot fully exploit such parallelism because they do not have mechanisms to dynamically detect such false inter-thread dependences. We propose Speculative Lock Elision (SLE), a novel micro-architectural technique to remove dynamically unnecessary lock-induced serialization and enable highly concurrent multithreaded execution. The key insight is that locks do not always have to be acquired for a correct execution. Synchronization instructions are predicted as being unnecessary and elided. This allows multiple threads to concurrently execute critical sections protected by the same lock. Misspeculation due to inter-thread data conflicts is detected using existing cache mechanisms and rollback is used for recovery. Successful speculative elision is validated and committed without acquiring the lock. SLE can be implemented entirely in microarchitecture without instruction set support and without system-level modifications, is transparent to programmers, and requires only trivial additional hardware support. SLE can provide programmers a fast path to writing correct high-performance multithreaded programs.

This paper presents and characterizes the Princeton Application Repository for Shared-Memory Computers (PARSEC), a benchmark suite for studies of Chip-Multiprocessors (CMPs). Previous available benchmarks for multiprocessors have focused on high-performance computing applications and used a limited number of synchronization methods. PARSEC includes emerging applications in recognition, mining and synthesis (RMS) as well as systems applications which mimic large-scale multithreaded commercial programs. Our characterization shows that the benchmark suite covers a wide spectrum of working sets, locality, data sharing, synchronization and off-chip traffic. The benchmark suite has been made available to the public.

This paper is motivated by the difficulty in writing correct high-performance programs. Writing shared-memory multithreaded programs imposes a complex trade-off between programming ease and performance, largely due to subtleties in coordinating access to shared data. To ensure correctness programmers often rely on conservative locking at the expense of performance. The resulting serialization of threads is a performance bottleneck. Locks also interact poorly with thread scheduling and faults, resulting in poor system performance.

This paper describes Embra, a simulator for the processors, caches, and memory systems of uniprocessors and cache-coherent multiprocessors. When running as part of the SimOS simulation environment, Embra models the processors of a MIPS R3000/R4000 machine faithfully enough to run a commercial operating system and arbitrary user applications. To achieve high simulation speed, Embra uses dynamic binary translation to generate code sequences which simulate the workload. It is the first machine simulator to use this technique. Embra can simulate real workloads such as multiprocess compiles and the SPEC92 benchmarks running on Silicon Graphic's IRIX 5.3 at speeds only 3 to 9 times slower than native execution of the workload, making Embra the fastest reported complete machine simulator. Dynamic binary translation also gives Embra the flexibility to dynamically control both the simulation statistics reported and the simulation model accuracy with low performance overheads. For example, Embra...

Hardly predictable data addresses in many irregular applications have rendered prefetching ineffective. In many cases, the only accurate way to predict these addresses is to directly execute the code that generates them. As multithreaded architectures become increasingly popular, one attractive approach is to use idle threads on these machines to perform pre-execution---essentially a combined act of speculative address generation and prefetching--- to accelerate the main thread. In this paper, we propose such a pre-execution technique for simultaneous multithreading (SMT) processors. By using software to control pre-execution, we are able to handle some of the most important access patterns that are typically difficult to prefetch. Compared with existing work on pre-execution, our technique is significantly simpler to implement (e.g., no integration of pre-execution results, no need of shortening programs for pre-execution, and no need of special hardware to copy register values upon thread spawns). Consequently, only minimal extensions to SMT machines are required to support our technique. Despite its simplicity, our technique offers an average speedup of 24% in a set of irregular applications, which is a 19% speedup over state-of-the-art software-controlled prefetching.

This article explores parallel processing on an alternative architecture, simultaneous multithreading (SMT), which allows multiple threads to compete for and share all of the processor's resources every cycle. The most compelling reason for running parallel applications on an SMT processor is its ability to use thread-level parallelism and instruction-level parallelism interchangeably. By permitting This research was supported by Digital Equipment Corporation, the Washington Technology Center, NSF PYI Award MIP-9058439, NSF grants MIP-9632977, CCR-9200832, and CCR9632769, DARPA grant F30602-97-2-0226, ONR grants N00014-92-J-1395 and N00014-94-11136, and fellowships from Intel and the Computer Measurement Group.