The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the ...

Randomization has proven to be a effective defense against conflict-based side-channel attacks in a shared cache. It improves security by assigning a unique randomization scheme to each security domain, e.g., though a different hashing function. However, ...

Modern large-scale recommender systems are built upon computation-intensive infrastructure and usually suffer from a huge difference in traffic between peak and off-peak periods. In peak periods, it is challenging to perform real-time computation for ...

Caching is a classic technique for improving system performance by reducing client-perceived latency and server load. However, cache management still needs to be improved and is even more difficult in multi-tenant systems. To shed light on these problems ...

In cloud gaming, interactive latency is one of the most important factors in users' experience. Although the interactive latency can be reduced through typical network infrastructures like edge caching and congestion control, the interactive latency of ...

Recently Graph Neural Networks (GNNs) have achieved great success in many applications. The mini-batch training has become the de-facto way to train GNNs on giant graphs. However, the mini-batch generation task is extremely expensive which slows down the ...

The limited cache size of GPU in general-purpose computing hinders the execution efficiency of thousands of concurrent threads. Several techniques have been proposed to increase the cache size per thread, such as repurposing shared memory and register ...

In database query processing, aggregation is an operator by which data with a common property is grouped and expressed in a summary form. Early aggregation is a popular method for improving the performance of the aggregation operator. In this paper, we ...

Caching techniques are widely used in the era of cloud computing from applications, such as Web caches to infrastructures, Memcached and memory caches in computer architectures. Prediction of cached data can greatly help improve cache management and hit ...

One critical challenge of designing an efficient prefetcher is to strike a balance between performance and hardware overhead. Some state-of-the-art prefetchers achieve very high performance at the price of a very large storage requirement, which makes ...

Virtual machine introspection (VMI) is the process of extracting knowledge about the inner state of a virtual machine from the outside. Traditional passive introspection mechanisms have proved themselves ineffective in many application domains due to ...

Skyrmion racetrack memory (SK-RM) has been regarded as a promising alternative to replace static random-access memory (SRAM) as a large-size on-chip cache device with high memory density. Different from other nonvolatile random-access memories (NVRAMs),...

The major impediment to scaling concurrent data structures is memory contention when accessing shared data structure access-points, leading to thread serialisation, hindering parallelism. Aiming to address this challenge, significant amount of work in ...

The explosive growth of modern web-scale applications has made cost-effectiveness a primary design goal for their underlying databases. As a backbone of modern databases, LSM-tree based key–value stores (LSM store) face limited storage options. They are ...

The on-chip memories of GPUs, including the register file, shared memory and L1 cache, can provide high bandwidth and low latency access for the temporary storage of data. The capacity of L1 cache can be increased by using the registers/shared memory ...

Nowadays, the surge of Internet contents and the need for high Quality of Experience (QoE) put the backbone network under unprecedented pressure. The emerging edge caching solutions help ease the pressure by caching contents closer to users. However, ...

The single-source shortest path (SSSP) problem is one of the most important and well-studied graph problems widely used in many application domains, such as road navigation, neural image reconstruction, and social network analysis. Although we have ...

Graph Neural Networks (GNNs) have achieved great success in downstream applications due to their ability to learn node representations. However, in many applications, graphs are not static. They often evolve with changes, such as the adjustment of node ...

Data-intensive applications dominated by random accesses to large working sets fail to utilize the computing power of modern processors. Graph random walk, an indispensable workhorse for many important graph processing and learning applications, is one ...

The high-profile Spectre attack and its variants have revealed that speculative execution may leave secret-dependent footprints in the cache, allowing an attacker to learn confidential data. However, existing static side-channel detectors either ignore ...