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HCW 2022 is one of the 24 workshops planned for the IPDPS 2022 conference.
TOPICS
Topics of interest include but are not limited to the following areas:
!!! SPECIAL TOPIC 1 !!! Heterogenous Integration of Quantum Computing: Future of computers will lead to a system that consists of both classical and Quantum computers for accelerated performance. Design, exploration, and analysis of architectures and software frameworks that enables and needs the heterogeneous integration of classical computing and Quantum computing. (e.g., heterogeneous quantum computers, error correction, heterogeneous applications that use both classical and quantum logic, benchmarks for heterogeneous quantum computers.)
!!! SPECIAL TOPIC 2 !!! Heterogeneity and Interoperability in SW & Data systems: Design, exploration, and analysis of architectures and software frameworks for interoperability in SW and Data systems. (e.g., semantic based frameworks, interoperability for heterogeneous IoT systems, model-driven frameworks.)
Heterogeneous multicore systems and architectures: Design, exploration, and experimental analysis of heterogeneous computing systems such as GPGPUs, heterogeneous systems-on-chip (SoC), accelerator systems (e.g., Intel Xeon Phi, AI chips such as Google’s TPUs), FPGAs, big.LITTLE, and application-specific architectures.
Heterogeneous parallel and distributed systems: Design and analysis of computing grids, cloud systems, hybrid clusters, datacenters, geo-distributed computing systems, and supercomputers.
Deep-memory hierarchies: Design and analysis of memory hierarchies with SRAM, DRAM, Flash/SSD, and HDD technologies; NUMA architectures; cache coherence strategies; novel memory systems such as phase-change RAM, magnetic (e.g., STT) RAM, 3D Xpoint/crossbars, and memristors.
On-chip, off-chip and heterogeneous network architectures: Network-on-chip (NoC) architectures and protocols for heterogeneous multicore applications; energy, latency, reliability, and security optimizations for NoCs; off-chip (chip-to-chip) network architectures and optimizations; heterogeneous networks (combination of NoC and off-chip) design, evaluation, and optimizations; large scale parallel and distributed heterogeneous network design, evaluation, and optimizations.
Programming models and tools: Programming paradigms and tools for heterogeneous systems; middleware and runtime systems; performance-abstraction tradeoff; interoperability of heterogeneous software environments; workflows; dataflows.
Resource management and algorithms for heterogeneous systems: Parallel algorithms for solving problems on heterogeneous systems (e.g., multicores, hybrid clusters, grids or clouds); strategies for scheduling and allocation on heterogeneous 2D and 3D multicore architectures; static and dynamic scheduling and resource management for large-scale and parallel heterogeneous systems.
Modeling, characterization, and optimizations: Performance models and their use in the design of parallel and distributed algorithms for heterogeneous platforms, characterizations and optimizations for improving the time to solve a problem (e.g., throughput, latency, runtime), modeling and optimizing electric consumption (e.g., power, energy); modeling for failure management (e.g., fault tolerance, recovery, reliability); modeling for security in heterogeneous platforms.
Applications on heterogeneous systems: Case studies; confluence of Big Data systems and heterogeneous systems; data-intensive computing; deep learning; scientific computing.
