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Showing 1 to 6 of 6 for “"Remote Direct Memory Access (RDMA)"”.
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Designing RDMA-based efficient Communication for GPU Remoting
… harness the computational capabilities of GPUs remotely. GVirtuS, a GPU Remoting software, facilitates transparent and hypervisor-independent access to GPGPUs within virtual machines. This research focuses on the middleware communication layer implemented in GVirtuS and presents a comprehensive …
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Delegation for Multi-Threaded and Rack-Scale Software
… object to a single designated owner instead of accessing the object directly. Because only the owner thread ever mutates the object, no locks are needed, other threads interact with it by sending requests. This avoids data races, simplifies reasoning, and can outperform lock-based designs by …
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Accelerating messages by avoiding copies using RDMA in an asynchronous parallel runtime system
… One sided communication with the help of Remote Direct Memory Access (RDMA) supported hardware is the natural choice for large messages as it has proven to provide reduced latencies and increased bandwidth for large payloads in High Performance Computing (HPC) networks. Using RDMA …
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Scaling RDMA RPCs with FLOCK
RDMA-capable networks are gaining traction with datacenter deployments due to their high throughput, low latency, CPU efficiency, and advanced features, such as remote memory operations. However, efficiently utilizing RDMA capability in a common setting of high fan-in, fan-out asymmetric network …
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Programming Abstractions for Scalable and High-Performance Memory Disaggregation
Memory-intensive applications, such as in-memory analytics, databases, and caching, are driving the memory demand in datacenters. Unfortunately, DRAM scaling is challenging as the technology reaches its physical limit. Although its demand continues to rise, memory is an underutilized resource …
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Building a columnar database on shared main memory-based storage
… a shared-nothing architecture. In contrast, main memory-based parallel database management systems are dominated solely by the shared-nothing approach as it preserves the in-memory performance advantage by processing data locally on each server. We argue that this unilateral development is going …