Knotted memories of a betrayed sacrifice: Rethinking trauma and hope in South Africa

Different groups within South African society express disillusionment with the present through a discourse of betrayal in relation to the liberation movement-cum-governing-party of the African National Congress. This article focuses on a particular articulation of this discourse within two memory communities in the Western Cape (Bonteheuwel and Crossroads) who were embroiled in violence and political struggle during apartheid and continue to suffer conditions of structural violence in the post-apartheid era. It analyses the shared memory narrative of a ‘betrayed sacrifice’ to demonstrate a proposed theoretical concept of ‘knotted memories’ which describes the way in which past and present memories of suffering knot together to produce a lived affective condition of despair. It further considers what these everyday experiences of ‘knotted memories’ mean for re-thinking the nature of trauma and hope in relation to post-apartheid despair.

‘Interrupting the Present’

A sense of repetition pervades contemporary South African political and cultural debate. Several recent studies have drawn attention to the fact that the renewed student protests since March 2015 parallel several features of the resistance and liberation movements of the 1970s and 1980s. At a pivotal position between the two moments of political struggle stands the ‘miracle’ of the peaceful transition in 1994. Within this set of circumstances a group of curators, artists, and writers, Gabi Ngcobo and Kemang Wa Lehulere, amongst others, formed a collective under the name CHR (Center for Historical Reenactments) in Johannesburg in 2010. The CHR has pursued several questions that interrogate the complexity of a shared memory bridging segregated Apartheid legacy: how do readings of the past inform contemporary urgencies, and what are the political potentials of artistic interpretations of histories? How do they participate in the formation of new subjectivities?

Deterministic Constant-Amortized-RMR Abortable Mutex for CC and DSM

The abortable mutual exclusion problem, proposed by Scott and Scherer in response to the needs in real-time systems and databases, is a variant of mutual exclusion that allows processes to abort from their attempt to acquire the lock. Worst-case constant remote memory reference algorithms for mutual exclusion using hardware instructions such as Fetch&Add or Fetch&Store have long existed for both cache coherent (CC) and distributed shared memory multiprocessors, but no such algorithms are known for abortable mutual exclusion. Even relaxing the worst-case requirement to amortized, algorithms are only known for the CC model. In this article, we improve this state of the art by designing a deterministic algorithm that uses Fetch&Store to achieve amortized O (1) remote memory reference in both the CC and distributed shared memory models. Our algorithm supports Fast Abort (a process aborts within six steps of receiving the abort signal) and has the following additional desirable properties: it supports an arbitrary number of processes of arbitrary names, requires only O (1) space per process, and satisfies a novel fairness condition that we call Airline FCFS . Our algorithm is short with fewer than a dozen lines of code.

Scalable Graphics Processing Unit–Based Multiscale Linear Solvers for Reservoir Simulation

Summary In this work, the scalability of two key multiscale solvers for the pressure equation arising from incompressible flow in heterogeneous porous media, namely, the multiscale finite volume (MSFV) solver, and the restriction-smoothed basis multiscale (MsRSB) solver, are investigated on the graphics processing unit (GPU) massively parallel architecture. The robustness and scalability of both solvers are compared against their corresponding carefully optimized implementation on the shared-memory multicore architecture in a structured problem setting. Although several components in MSFV and MsRSB algorithms are directly parallelizable, their scalability on the GPU architecture depends heavily on the underlying algorithmic details and data-structure design of every step, where one needs to ensure favorable control and data flow on the GPU, while extracting enough parallel work for a massively parallel environment. In addition, the type of algorithm chosen for each step greatly influences the overall robustness of the solver. Thus, we extend the work on the parallel multiscale methods of Manea et al. (2016) to map the MSFV and MsRSB special kernels to the massively parallel GPU architecture. The scalability of our optimized parallel MSFV and MsRSB GPU implementations are demonstrated using highly heterogeneous structured 3D problems derived from the SPE10 Benchmark (Christie and Blunt 2001). Those problems range in size from millions to tens of millions of cells. For both solvers, the multicore implementations are benchmarked on a shared-memory multicore architecture consisting of two packages of Intel® Cascade Lake Xeon Gold 6246 central processing unit (CPU), whereas the GPU implementations are benchmarked on a massively parallel architecture consisting of NVIDIA Volta V100 GPUs. We compare the multicore implementations to the GPU implementations for both the setup and solution stages. Finally, we compare the parallel MsRSB scalability to the scalability of MSFV on the multicore (Manea et al. 2016) and GPU architectures. To the best of our knowledge, this is the first parallel implementation and demonstration of these versatile multiscale solvers on the GPU architecture. NOTE: This paper is published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.