The ALPBench benchmark suite for complex multimedia applications. Multimedia applications are becoming increasingly important for a large class of general-purpose processors. Contemporary media applications are highly complex and demand high performance. A distinctive feature of these applications is that they have significant parallelism, including thread- , data-, and instruction-level parallelism, that is potentially well-aligned with the increasing parallelism supported by emerging multi-core architectures. Designing systems to meet the demands of these applications therefore requires a benchmark suite comprising these complex applications and that exposes the parallelism present in them. This paper makes two contributions. First, it presents ALPBench, a publicly available benchmark suite that pulls together five complex media applications from various sources: speech recognition (CMU Sphinx 3), face recognition (CSU), ray tracing (Tachyon), MPEG-2 encode (MSSG), and MPEG-2 decode (MSSG). We have modified the original applications to expose thread-level and data-level parallelism using POSIX threads and sub-word SIMD (Inters SSE2) instructions respectively. Second, the paper provides a performance characterization of the ALPBench benchmarks, with a focus on parallelism. Such a characterization is useful for architects and compiler writers for designing systems and compiler optimizations for these applications.

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  1. Dai, H. K.; Wang, Z.: Two parallel algorithms for finding all minimal maximum subsequences (2019)
  2. Cebrian, Juan M.; Jahre, Magnus; Natvig, Lasse: ParVec: vectorizing the PARSEC benchmark suite (2015)
  3. Sánchez, Daniel; Cebrián, Juan M.; García, José M.; Aragón, Juan L.: Soft-error mitigation by means of decoupled transactional memory threads (2015) ioport
  4. Fensch, Christian; Cintra, Marcelo: An evaluation of an OS-based coherence scheme for tiled CMPs (2011) ioport
  5. Harmanci, Derin; Gramoli, Vincent; Felber, Pascal; Fetzer, Christof: Extensible transactional memory testbed (2010)