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While high-end heterogeneous systems are increasingly supporting heterogeneous uniform memory access (hUMA) as envisioned by the Heterogeneous System Architecture (HSA) foundation, their low-power counterparts targeting the embedded domain still lack basic features like virtual memory support for accelerators. As opposed to simply passing virtual address pointers, explicit data management involving...
The main goal of the ANTAREX project is to express by a Domain Specific Language (DSL) the application self-adaptivity and to runtime manage and autotune applications for green and heterogeneous High Performance Computing (HPC) systems up to the Exascale level. Key innovations of the project include the introduction of a separation of concerns between self-adaptivity strategies and application functionalities...
This work describes how we use High-Level Synthesis to support design space exploration (DSE) of heterogeneous many-core systems. Modern embedded systems increasingly couple hardware accelerators and processing cores on the same chip, to trade specialization of the platform to an application domain for increased performance and energy efficiency. However, the process of designing such a platform is...
Modern designs for embedded systems are increasingly embracing cluster-based architectures, where small sets of cores communicate through tightly-coupled shared memory banks and high-performance interconnections. At the same time, the complexity of modern applications requires new programming abstractions to exploit dynamic and/or irregular parallelism on such platforms. Supporting dynamic parallelism...
Modern designs for embedded many-core systems increasingly include application-specific units to accelerate key computational kernels with orders-of-magnitude higher execution speed and energy efficiency compared to software counterparts. A promising architectural template is based on heterogeneous clusters, where simple RISC cores and specialized HW units (HWPU) communicate in a tightly-coupled manner...
Modern embedded MPSoC designs increasingly couple hardware accelerators to processing cores to trade between energy efficiency and platform specialization. To assist effective design of such systems there is the need on one hand for clear methodologies to streamline accelerator definition and instantiation, on the other for architectural templates and run-time techniques that minimize processors-to-accelerator...
Several recent many-core accelerators have been architected as fabrics of tightly-coupled shared memory clusters. A hierarchical interconnection system is used - with a crossbar-like medium inside each cluster and a network-on-chip (NoC) at the global level - which make memory operations non-uniform (NUMA). Nested parallelism represents a powerful programming abstraction for these architectures, where...
P2012 is an area- and power-efficient many-core computing accelerator based on multiple globally asynchronous, locally synchronous processor clusters. Each cluster features up to 16 processors with independent instruction streams sharing a multi-banked one-cycle access L1 data memory, a multi-channel DMA engine and specialized hardware for synchronization and aggressive power management. P2012 is...
P2012 is an area- and power-efficient many-core computing fabric based on multiple globally asynchronous, locally synchronous (GALS) clusters supporting aggressive fine-grained power, reliability and variability management. Clusters feature up to 16 processors and one control processor with independent instruction streams sharing a multi-banked L1 data memory, a multi-channel DMA engine, and specialized...
Emerging TSV-based 3D integration technologies have shown great promise to overcome scalability limitations in 2D designs by stacking multiple memory dies on top of a many-core die. Application software developers need programming models and tools to fully exploit the potential of vertically stacked memory. In this work, we focus on efficient data mapping for SPMD parallel applications on an explicitly...
Our work focuses on allocating and scheduling a synchronous data-flow (SDF) graph onto a multi-core platform subject to a minimum throughput requirement. This problem has traditionally be tackled by incomplete approaches based on problem decomposition and local search, which could not guarantee optimality. Exact algorithms used to be considered reasonable only for small problem instances. We propose...
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