The current trend towards multi/many-core computing architectures requires a global rethinking of software development and hardware design. The PARMA-DITAM workshop focuses on parallel programming models, design space exploration and tools, and run-time management techniques to exploit the features of multi/manycore computing architectures. It is centered on six main topics that cover: (i) parallel programming models and languages, compilers and virtualization techniques; (ii) runtime adaptivity, runtime management, power management and memory management; (iii) heterogeneous and reconfigurable many-core architectures and design space exploration; (iv) design tools and methodologies for many-core architectures; (v) parallel applications for many-core platforms and (vi) energy-efficient microservers and autotuning techniques for heterogeneous HPC applications.
Proceeding Downloads
Stack size estimation on machine-independent intermediate code for OpenCL kernels
Stack size is an important factor in the mapping decision when dealing with embedded heterogeneous architectures, where fast memory is a scarce resource. Trying to map a kernel onto a device with insufficient memory may lead to reduced performance or ...
Predictive modeling methodology for compiler phase-ordering
Today's compilers offer a huge number of transformation options to choose among and this choice can significantly impact on the performance of the code being optimized. Not only the selection of compiler options represents a hard problem to be solved, ...
Flexible resource allocation and management for application graphs on ReNÉ MPSoC
Performance of an application on a many-core machine primarily hinges on the ability of the architecture to exploit parallelism and to provide fast memory accesses. Exploiting parallelism in static application graphs on a multicore target is relatively ...
Low communication overhead dynamic mapping of multiple HEVC video stream decoding on NoCs
The High Efficiency Video Coding (HEVC) standard offers several parallelisation tools such as wave-front parallel processing (WPP) and Tiles (independent frame regions) to better manage the computationally expensive workloads on modern multicore/many-...
Deploying and monitoring hadoop MapReduce analytics on single-chip cloud computer
Modern data analytics applications exhibit scale-out characteristics, requiring large amount of computational power. Recent research has shown that modern manycore architectures forms a promising platform solution for this emerging type of workloads. In ...
Runtime resource management for embedded and HPC systems
Resource management is a well known problem in almost every computing system ranging from embedded to High Performance Computing (HPC) and is useful to optimize multiple orthogonal system metrics such as power consumption, performance and reliability. ...
- Proceedings of the 7th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and the 5th Workshop on Design Tools and Architectures For Multicore Embedded Computing Platforms
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
PARMA-DITAM'2020 | 9 | 5 | 56% |
PARMA-DITAM '17 | 15 | 6 | 40% |
Overall | 24 | 11 | 46% |