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Virtual memory has been a standard hardware feature for more than three decades. At the price of increased hardware complexity, it has simplified software and promised strong isolation among colocated processes. In modern computing systems, however, the costs of virtual memory have increased significantly. With large memory workloads, virtualized environments, data center computing, and chips with multiple DMA devices, virtual memory can degrade performance and increase power usage. We therefore explore the implications of building applications and operating systems without relying on hardware support for address translation. Primarily, we investigate the implications of removing the abstraction of large contiguous memory segments. Our experiments show that the overhead to remove this reliance is surprisingly small for real programs. We expect this small overhead to be worth the benefit of reducing the complexity and energy usage of address translation. In fact, in some cases, performance can even improve when address translation is avoided.
The current mobile applications have rapidly growing memory footprints, posing a great challenge for memory system design. Insufficient DRAM main memory will incur frequent data swaps between memory and storage, a process that hurts performance, cons
Computers continue to diversify with respect to system designs, emerging memory technologies, and application memory demands. Unfortunately, continually adapting the conventional virtual memory framework to each possible system configuration is chall
Even with generational improvements in DRAM technology, memory access latency still remains the major bottleneck for application accelerators, primarily due to limitations in memory interface IPs which cannot fully account for variations in target ap
Hybrid memory systems, comprised of emerging non-volatile memory (NVM) and DRAM, have been proposed to address the growing memory demand of applications. Emerging NVM technologies, such as phase-change memories (PCM), memristor, and 3D XPoint, have h
Secure Computation (SC) is a family of cryptographic primitives for computing on encrypted data in single-party and multi-party settings. SC is being increasingly adopted by industry for a variety of applications. A significant obstacle to using SC f