vCAT: Dynamic Cache Management Using CAT Virtualization

Abstract

This paper presents vCAT, a novel design for dynamic shared cache management on multicore virtualization platforms based on Intel's Cache Allocation Technology (CAT). Our design achieves strong isolation at both task and VM levels through cache partition virtualization, which works in a similar way as memory virtualization, but has challenges that are unique to cache and CAT. To demonstrate the feasibility and benefits of our design, we provide a prototype implementation of vCAT, and we present an extensive set of microbenchmarks and performance evaluation results on the PARSEC benchmarks and synthetic workloads, for both static and dynamic allocations. The evaluation results show that (i) vCAT can be implemented with minimal overhead, (ii) it can be used to mitigate shared cache interference, which could have caused task WCET increased by up to 7.2 x, (iii) static management in vCAT can increase system utilization by up to 7 x compared to a system without cache management; and (iv) dynamic management substantially outperforms static management in terms of schedulable utilization (increase by up to 3 x in our multi-mode example use case). Abstract-This paper presents vCAT, a novel design for dynamic shared cache management on multicore virtualization platforms based on Intel's Cache Allocation Technology (CAT). Our design achieves strong isolation at both task and VM levels through cache partition virtualization, which works in a similar way as memory virtualization, but has challenges that are unique to cache and CAT. To demonstrate the feasibility and benefits of our design, we provide a prototype implementation of vCAT, and we present an extensive set of microbenchmarks and performance evaluation results on the PARSEC benchmarks and synthetic workloads, for both static and dynamic allocations. The evaluation results show that (i) vCAT can be implemented with minimal overhead, (ii) it can be used to mitigate shared cache interference, which could have caused task WCET increased by up to 7.2×, (iii) static management in vCAT can increase system utilization by up to 7× compared to a system without cache management; and (iv) dynamic management substantially outperforms static management in terms of schedulable utilization (increase by up to 3× in our multi-mode example use case). Disciplines Computer Engineering | Computer Sciences

MemJam: A False Dependency Attack Against Constant-Time Crypto Implementations

“…The aforementioned constant-time implementation of AES is part of the SGX SDK source code. • Protection Bypass: Bypasses of remarkable protections such as proposals based on constant-time techniques [7,24], static and runtime analysis [27,28] and cache architecture [29,30,31,32].…”

“…In particular, introducing redundancy and randomness to the S-Box tables for AES has been proposed [18]. A custom memory manager [40], relaxed inclusion caches [31] and solutions based on cache allocation technology (CAT) such as Catalyst [29] and vCat [32] are proposed to defend against LLC contention. Sanctum [30] and Ozone [41] are new processor designs with respect to cache attacks.…”

The need for deterministic virtualization in the industrial internet of things

“…Xu et al [25] target minimization of resource contention due to shared LLCs. They propose vCAT that utilizes Intel's Cache Allocation Technology (CAT) [3] to provide virtual cache partitions.…”

“…Xen with the RTDS scheduler and vCAT can provide reasonable hard real-time performance under the assumption that there exists a schedule according to CST for a predefined set of VMs with known resource requirements [24,25]. As a result, even though Xen is capable of dynamic VM management, creating VMs during runtime diminishes hard real-time guarantees since resource requirements and the system utilization changes.…”

Holistic Resource Allocation for Multicore Real-Time Systems

“…Cache resource. Several cache partitioning techniques have been proposed to reduce the shared cache interference [9,21,22,26,28,59,61,62,68,74]. The software-based approach reorganizes a task's memory layout to allocate a specific cache area to the task using, e.g., page coloring [28,39,67] or compiler-based [42] techniques.…”