NCSA Strategic Retreat: System Software Trends Bill Gropp

Driving Forces Hardware – Power constraints have limited clock speeds; no significant increase since 2006 or expected for the next 5-10 years – Multicore/manycore makes everything parallel – Changes in memory architecture (performance, power) – Heterogeneous processing elements (currently GPGPUs, later different elements on processor die) – Disk size makes TB a typical student laptop disk – Concern about Fault rate Software – Complexity of software in applications Algorithms – Complexity of applications in software

Trends in Software Programming Languages/Models Operating Systems File Systems Development Environments

Programming Models and Languages Node programming – Algorithm/domain specific for multicore systems (e.g., TBB) – GPGPUs (X + OpenCL) – Autotuning; source to source transformations – Scripting, multilingual programming (Distributed Memory) Parallel programming – The usual suspects MPI; MPI + hybrid (threaded) model PGAS (UPC, CAF); next Gen (Chapel, X10+, Fortress…) GA, SHMEM, … – New(ish) Parallel Data processing models/languages – MapReduce (Hadoop) – DAGs (DryadLinq)

Operating Systems Light-weight for appliances (e.g., iPad) Low-jitter for MPP – Less than single system image, but some coordinated activities Scalability to SMP Virtualization (Hypervisors) Security and robustness

File Systems Tweeks on POSIX API – Shared (“global file system”) – Performance, robustness variations – Non-POSIX API (parallel update semantics, e.g.) – ACLs Data bases; Systems for data processing – Google file system etc. Alternative persistent store models – Not a byte-stream model – Access methods within object/class Hierarchical systems

Development Environments “Domain specific” languages IDE – Eclipse Frameworks and libraries – Application areas Debuggers See programming languages (e.g., multilingual applications)

Summary Most likely direction – HPC – Business as usual, with increased use of automation in code generation and tuning – Scalability issues will drive changes in commodity systems, but not necessarily in directions needed by HPC applications (see Linux Thread Scheduler) – New data management, possibly with low-level support Exascale directions add – Fault tolerance becomes critical – Latency hiding/tolerances becomes critical