Opening Session

• Sebastian Lopienski (CERN)
• Enrica Maria Porcari (CERN)

Self-presentation: 1 minute per person

Preparing for the HL-LHC computational challenge (Introduction lecture)

• Danilo Piparo (CERN)

In this talk we will introduce some basic concepts related to HEP data processing and analysis workflows, seeing them in action in the context of LHC experiments. We’ll also talk about the evolution of the LHC accelerator and experiments. We’ll characterise at a high level what are the consequences of those upgrades for the HEP data processing software, in particular in the context of an evolving hardware and computing infrastructure.

Introduction to efficient computing (Track 1: Technologies and Platforms)

• Andrzej Nowak

Technologies and Platforms - lecture 1 - The evolution of computing hardware and what it means in practice - The seven dimensions of performance - Controlling and benchmarking your computer and software - Software that scales with the hardware - Advanced performance tuning in hardware

Self-presentation: 1 minute per person

Hardware evolution and heterogeneity (Track 1: Technologies and Platforms)

• Andrzej Nowak

Technologies and Platforms - lecture 2 - Accelerators, co-processors, heterogeneity - Memory architectures, hardware caching and NUMA - Compute devices: CPU, GPU, FPGA, ASIC etc. - The role of compilers

Technologies and Platforms - exercise (Track 1: Technologies and Platforms)

• Andrzej Nowak

Data-oriented design (Track 1: Technologies and Platforms)

• Andrzej Nowak

Technologies and Platforms - lecture 3 - Hardware vectorization in detail – theory vs. practice - Software design for vectorization and smooth data flow - How can compilers and other tools help?

Writing parallel software (Track 2: Parallel and Optimised Scientific Software)

• Sebastien Ponce (CERN)

Parallel and Optimised Scientific Software - lecture 1 - Amdahl's and Gustafson's laws - Asynchronous execution - Finding concurrency, task vs. data parallelism - Using threading in C++ and Python, comparison with multi-process - Resource protection and thread safety - Locks, thread local storage, atomic operations

Announcements

Modern programming languages for HEP (Track 2: Parallel and Optimised Scientific Software)

• Sebastien Ponce (CERN)

Parallel and Optimised Scientific Software - lecture 2 - Why Python and C++ ? - Recent evolutions: C++ 11/14/17 - Modern features of C++ related to performance - Templating versus inheritance, pros and cons of virtual inheritance - Python 3, and switching from Python 2

Technologies and Platforms - exercise (Track 1: Technologies and Platforms)

Technologies and Platforms - exercise debriefing (Track 1: Technologies and Platforms)

• Andrzej Nowak

Optimizing existing large codebase (Track 2: Parallel and Optimised Scientific Software)

• Sebastien Ponce (CERN)

Parallel and Optimised Scientific Software - lecture 3 - Measuring performance, tools and key indicators - Improving memory handling - The nightmare of thread safety - Code modernization and low level optimizations - Data structures for efficient computation in modern C++

Optimizing existing large codebase - exercise (Track 2: Parallel and Optimised Scientific Software)

• Sebastien Ponce (CERN)

Optimisation of an existing, production grade large codebase

Scientific computing on heterogeneous architectures (Track 3: Programming for Heterogeneous Architectures)

• Dorothea Vom Bruch (CPPM/CNRS)

Programming for Heterogeneous Architectures - lecture 1 - Introduction to heterogeneous architectures and the performance challenge - From general to specialized: Hardware accelerators and applications - Type of workloads ideal for different accelerators - Trade-offs between multi-core and many-core architectures - Implications of heterogeneous hardware on the design and architecture of scientific software - Embarrassingly parallel scientific applications in HPC and CERN

Announcements

Student lightning talks

Practical vectorization (Track 2: Parallel and Optimised Scientific Software)

• Sebastien Ponce (CERN)

Parallel and Optimised Scientific Software - lecture 4 - Measuring vectorization level - What to expect from vectorization - Preparing code for vectorization - Vectorizing techniques in C++: intrinsics, libraries, autovectorization

School photo

Programming for GPUs (Track 3: Programming for Heterogeneous Architectures)

• Dorothea Vom Bruch (CPPM/CNRS)

Programming for Heterogeneous Architectures - lecture 2 - From SIMD to SPMD, a programming model transition - Thread and memory organization - Basic building blocks of a GPU program - Control flow, synchronization, atomics

Announcements

Performant programming for GPUs (Track 3: Programming for Heterogeneous Architectures)

• Daniel Campora (University of Maastricht)

Programming for Heterogeneous Architectures - lecture 3 - Data locality, coalesced memory accesses, tiled data processing - GPU streams, pipelined memory transfers - Under the hood: branchless, warps, masked execution - Debugging and profiling a GPU application

Practical vectorization - exercise (Track 2: Parallel and Optimised Scientific Software)

• Sebastien Ponce (CERN)

Optimisation + vectorization - exercise debriefing (Track 2: Parallel and Optimised Scientific Software)

• Sebastien Ponce (CERN)

Design patterns and best practices (Track 3: Programming for Heterogeneous Architectures)

• Daniel Campora (University of Maastricht)

Programming for Heterogeneous Architectures - lecture 4 - Good practices: single precision, floating point rounding, avoid register spilling, prefer single source - Other standards: SYCL, HIP, OpenCL - Middleware libraries and cross-architecture compatibility - Reusable parallel design patterns with real-life applications

Programming for heterogeneous architectures - exercise (Track 3: Programming for Heterogeneous Architectures)

• Daniel Campora (University of Maastricht)
• Dorothea Vom Bruch (CPPM/CNRS)

Programming for heterogeneous architectures - exercise (Track 3: Programming for Heterogeneous Architectures)

Programming for heterogeneous architectures - exercise (Track 3: Programming for Heterogeneous Architectures)

Announcements

Programming for heterogeneous architectures - exercise debriefing (Track 3: Programming for Heterogeneous Architectures)

• Daniel Hugo Campora Perez (University of Maastricht)
• Dorothea Vom Bruch (CPPM/CNRS)

Summary and future technologies overview (Track 1: Technologies and Platforms)

• Andrzej Nowak

Technologies and Platforms - lecture 4 - Teaching program summary and wrap-up - Next-generation memory technologies and interconnect - Future computing evolution

Exam

Closing Session

• Sebastian Lopienski (CERN)