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

Over the last decade, significant advances have been made in compilation technology for capitalizing on instruction-level parallelism (ILP). The vast majority of ILP compilation research has been conducted in the context of generalpurpose computing, and more specifically the SPEC benchmark suite

by performance over another class. These theorems result in a geometric interpretation of what it means for an algorithm to be well suited to an optimization problem. Applications of the NFL theorems to information-theoretic aspects of optimization and benchmark measures of performance are also presented. Other

of Water from the SPLASH benchmark suite, we achieved only moderate speedups (4.0) due to the high communication and synchronization rate. Speedups decline on the 10-Mbps Ethernet (5.5 for Jacobi, 6.5 for TSP, 4.2 for Quicksort, 5.1 for ILINK, and 2.1 for Water), reflecting the bandwidth limitations

use methodologies developed for C, C++, and Fortran. SPEC, the dominant purveyor of benchmarks, compounded this problem by institutionalizing these methodologies for their Java benchmark suite. This paper recommends benchmarking selection and evaluation methodologies, and introduces the Da

synthetic traffic and traces from the SPLASH-2 benchmark suite show reduction in packet latency by up to 77.1 % with upto 39.6 % reduction in average router energy consumption as compared to a state-of-theart baseline packet-switched design. For the same saturation throughput as the baseline network, TFC

lmbench: Portable tools for performance analysis lmbench is a micro-benchmark suite designed to focus attention on the basic building blocks of many common system applications, such as databases, simulations, software development, and networking. In almost all cases, the individual tests

functioning or change to it. Unlike stratification, MetaCost is applicable to any number of classes and to arbitrary cost matrices. Empirical trials on a large suite of benchmark databases show that MetaCost almost always produces large cost reductions compared to the cost-blind classifier used (C4.5RULES

SQL implementation. We also hope to foster the development of additional cloud benchmark suites that represent other classes of applications by making our benchmark tool available via open source. In this regard, a key feature of the YCSB framework/tool is that it is extensible—it supports easy definition of new

This paper presents and characterizes Rodinia, a benchmark suite for heterogeneous computing. To help architects study emerging platforms such as GPUs (Graphics Processing Units), Rodinia includes applications and kernels which target multi-core CPU and GPU platforms. The choice of applications